Lila Sciences jobs

Co-op, Protein Sciences Cambridge, MA USA Your Impact at LILA Lila Sciences is seeking a dedicated Cell Free Co-op for Protein Sciences to join our team. The focus of this role will be cell culture and cell lysis to generate materials for protein expression. You will continue maintenance and optimization of the cell free platform here at Lila. What You'll Be Building - Perform cell culture and lysis of various cell lines - Generate quality control data via plate-based assays - Prepare media and solutions for cell culture and processing - Track and maintain excellent data records in formats amenable to computational workflows - Analyze and interpret experimental data, prepare technical reports, and present findings to internal teams and stakeholders What You'll Need to Succeed - Working on a degree in biochemistry, molecular biology, biotechnology, biological engineering, chemical engineering, or a related field. - 1+ years of laboratory experience - Experience with cell culture techniques, including growth, maintenance, and transformation - Excellent attention to detail, organization, and communication Bonus Points For - An enthusiasm for and openness to using AI in laboratory settings is highly valued - Familiarity with plate-based assays is a plus - Familiarity with Python programming for data analysis and automation is a plus About LILA Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models

Research Associate, Protein Science, Cell-Free Expression Cambridge, MA USA Your Impact at LILA Lila is seeking a dedicated and skilled Research Associate, Protein Sciences to join our high through-put Cell-Free Expression platform. As a Research Associate, you will play a vital role in our interdisciplinary research efforts focused on building and automating artificial intelligence-driven processes across a variety of valuable applications. What You'll Be Building - Development and refinement of cell-free expression systems for efficient protein synthesis. - Optimize conditions for high-yield and high-quality protein production - Prepare media and solutions for cell culture and processing - Perform molecular cloning, mutagenesis, and other genetic manipulation for strain development. - Demonstrate proficiency in operating and utilizing liquid handlers and robotic systems for automated laboratory processes. - Collaborate with biologists, machine learning scientists, software developers, and other engineers to develop and optimize AI-driven processes. - Track and maintain excellent data records in formats amenable to computational workflows. - Analyze and interpret experimental data, prepare technical reports, and present findings to internal teams and stakeholders. What You'll Need to Succeed - A bachelor's or master's degree in biochemistry, molecular biology, biotechnology, biological engineering, chemical engineering, or a related field. - 1-3 years of laboratory experience - Experience with cell culture techniques, including growth, maintenance, and transformation, across a variety of cell lines - Familiarity with plate-based assays - Excellent attention to detail, organization, and communication Bonus Points For - Skilled in cloning, expression and optimization of protein - Data analysis using relevant software

Co-Op, Data Extraction Cambridge, MA USA Your Impact at LILA Lila Sciences builds AI systems that accelerate discovery across the physical and life sciences. Within Physical Sciences AI, our team works on turning unstructured scientific knowledge (e.g., literature, patents, technical reports) into structured signals that power downstream Lila applications. As a Data Extraction Co-Op, you will work alongside research scientists and engineers on a focused sub-problem in this stack. You will get hands-on experience fine-tuning and evaluating extraction models, building pipelines for messy real-world data, and shipping work that flows into production systems. What You'll Be Building - Contribute to AI systems that extract and structure knowledge from scientific literature and patents, focused on a well-defined sub-problem - Fine-tune and evaluate language, multimodal, or specialized models for data extraction, with mentor guidance - Build and test pipelines that structure unstructured scientific data across text, tables, and visuals - Run extraction pipelines, analyze results, and document findings clearly - Share your work through a team presentation, write-up, or contribution to a publication or open-source project What You'll Need to Succeed - Pursuing a Bachelor's, Master's, or PhD in Computer Science, Chemistry, Materials Science, or a related field - Solid foundation in machine learning fundamentals and Python - Familiarity with NLP or computer vision concepts - Curiosity about scientific data and willingness to learn quickly in a research setting Bonus Points For - Coursework or projects involving multimodal models or document understanding (OCR, table/figure extraction) - Experience working with messy, real-world datasets

Vice President, Engineering Cambridge, MA USA Your Impact at LILA As Lila scales its AI Science Factories globally, the VP of Engineering will create and sustain an engineering model for a unified, scalable platform for autonomous experimentation. This role will be responsible for defining and implementing that platform across hardware, automation, and systems engineering. This executive will own strategy, execution, and talent across Lila's systems, hardware, and automation engineering. The role sits on the senior leadership team, reports directly to the Chief Autonomous Science Officer, and interfaces directly with Robotics, Software, Operations, and Science teams. The VP Engineering will bring deep technical experience in automation of lab science, a track record of building and leading multi-disciplinary engineering organizations, mentorship practices that foster career development of engineers at all levels, and the judgment to balance near-term delivery with long-term platform development. This is a hands-on leadership role in a fast-moving environment, requiring brilliance and dynamism to realize autonomous experimentation across materials science, chemistry, and life science. The role requires engineering innovations to achieve an unprecedented depth of AI integration in lab science, which combined with aggressive scaling of Lila's AI Science Factories (AISFs) will produce the highest degree of scientific intelligence on earth. What You'll Be Building - Set the engineering roadmap for ASP Engineering, including objectives, risks, and platform priorities via collaboration with the Robotics, Software, Science, and Product teams. - Define and drive a unified platform architecture across hardware, automation, and systems engineering, reducing one-off designs and enabling repeatable

Scientist I/II, mRNA Translation Dynamics Cambridge, MA USA Your Impact at LILA We are seeking a curious, driven, and collaborative Scientist to join our discovery platform team focused on decoding mRNA translation dynamics. You will develop workflows that utilize next-generation pooled screening strategies like polysome profiling and Ribo-seq to to generate rich biological datasets that feed directly into Lila's machine learning models. This is a unique opportunity to help invent a new approach to biological discovery by integrating synthetic biology, high-throughput experimentation, and intelligent automation. What You'll Be Building - Design and execute high-throughput pooled screening campaigns to interrogate mRNA translation dynamics across diverse sequence and structural contexts - Develop and optimize cell-free and in-cell assay systems for quantitative measurement of translation efficiency, kinetics, and regulation across different cell environments - Collaborate closely with computational and ML teams to define data requirements, validate model predictions, and close the loop between experiment and prediction - Establish and refine next-generation library design strategies, leveraging combinatorial and rational approaches to explore sequence space efficiently - Analyze and interpret complex biological datasets, distilling key findings into actionable insights for platform advancement - Contribute to the development of automated and semi-automated experimental pipelines to increase throughput and consistency What You'll Need to Succeed - MSc with 4+ years of industry or academic experience, or PhD in a relevant field (molecular biology, bioengineering, synthetic biology, chemical biology, etc.) - Deep expertise in mRNA biology and translation regulation - Experience with next-generation sequencing based assays of mRNA

Platform Scientist, Soft Materials Cambridge, MA USA Your Impact at LILA Lila Sciences is seeking Platform Scientists, Soft Materials Focus to ideate, prototype, and transfer new experimental concepts for AI Science Factories targeting complex and soft material systems. In this role, you will work at the forefront of scientific ideation-partnering with a broad range of chemistry, materials, and AI teams to define new approaches to formulation, structure-property relationships, and performance evaluation. You will translate these concepts into scalable experimental workflows, custom apparatus, and software-enabled systems for autonomous research. What You'll Be Building - Collaborate with diverse scientific teams to ideate new experimental strategies for soft and complex materials, including formulations, colloids, polymers, gels, and biological or hybrid systems - Lead conceptual development of characterization and performance workflows leveraging techniques such as SAXS, SANS, rheology, and formulation performance assays - Design, prototype, and validate custom apparatus, experimental methods, and software tools to realize these concepts - Develop and refine workflows that connect structure, dynamics, and performance across multiple length and time scales - Transfer successful prototypes into production-ready systems within Lila's AI Science Factory platform, enabling autonomous experimentation What You'll Need to Succeed - MS or PhD in Materials Science, Chemistry, Chemical Engineering, Physics, or a related field, with a focus on soft or complex materials - Demonstrated experience collaborating across scientific disciplines to generate and refine experimental concepts - Hands-on experience with one or more of the following: SAXS, SANS, rheology, formulation performance or functional assays - Experience designing and

Director / Senior Director of New Product Planning,Physical Science Cambridge, MA USA Your Impact at LILA Lila Sciences is hiring a Director / Senior Director, New Product Planning of Physical Science to help shape Lila Origins, our company and asset creation arm which partners to translate scientific vision into molecules, materials, and real-world ventures. As a member of a small, highly cross-functional team, this role brings the commercial voice to life. The focus is on assessing where Lila's platform can produce differentiated assets and shaping how those opportunities become ventures, partnerships, or programs. What You'll Be Building - Source and evaluate new physical science opportunities for Origins, screening for scientific differentiation, commercial viability, and fit with Lila's platform capabilities - Track materials science, chemistry, energy systems, and advanced manufacturing trends, including platform breakthroughs, pipeline movement, and deal activity across deep tech and industry, and translate signal into actionable views for Origins - Match materials platforms and chemical or physical process innovations to application areas using technical rationale, competitive landscape, and unmet need, and recommend where Origins should concentrate effort - Build and own market sizing, end-market demand, and deal economic models that inform go / no-go decisions on candidate ventures and partnerships - Develop specifications and early commercial theses for assets under consideration, in partnership with Science, Product, and Corporate Development - Run primary and secondary research including expert interviews, competitor tracking, and customer and supply chain landscape analysis to stress-test assumptions and sharpen recommendations - Shape deal structures and

AI Residency Program, Material Science (2026 Cohort) Cambridge, MA USA AI Resident - 2026 Cohort The AI Residency Program is a full-time research opportunity designed to bridge the gap between academic research and industry applications in AI for materials science . Residents will work closely with Lila scientists and engineers on high-impact, open-science projects, with the option to focus on either fundamental or applied research. - Duration: 6-12 months (extension possible) - Start Dates: First hires beginning January 2026 , with rolling applications and additional intakes in Summer and Fall 2026 - Cohort Size: Small group of selected residents - Mentorship: Pairing with technical mentors, feedback from cross-functional teams - Resources: Access to proprietary datasets, high-performance compute, and Lila's research infrastructure Research areas include ML-accelerated simulations, Bayesian methods, representation learning, generative models, agentic science, and ML-driven automation. Application Requirement: Please submit your resume alongside a research proposal (up to 3 pages, unlimited references) outlining the project you would plan to pursue during your residency at Lila Sciences. Please submit your research proposal as your cover letter. Applications without both documents will not be considered. Optional supporting materials (e.g., recommendation letters, publications, research artifacts) may also be included. Your Impact at Lila The Lila Sciences AI Residency is a full-time research program at the intersection of artificial intelligence and materials science. As a resident, you'll join a cohort of researchers tackling open-ended scientific challenges alongside Lila's world-class team of scientists and engineers. With access to proprietary datasets, high-performance compute infrastructure, and

Research Scientist, Frontier Capabilities Cambridge, MA USA; San Francisco, CA USA Your impact at LILA We're building a talent-dense, high-agency research team to develop the next generation of learning systems and reasoning algorithms for agentic LLMs. Our work sits at the intersection of large language models, post-training, and scientific reasoning, with the goal of enabling systems that learn from experience, reason effectively, and improve through interaction . Scientific domains present a distinct set of challenges that make this problem uniquely hard. Feedback is sparse and delayed - experiments take days or weeks, not milliseconds. Ground truth is expensive or contested. Distribution shift is structural, as instruments, techniques, and knowledge bases evolve continuously. The hypothesis space is vast and reward signal is thin. Existing benchmark do not capture these nuances. The goal is to build systems that can operate effectively in this scientific regime. This role spans a few complementary directions. Candidates are expected to bring deep expertise in one (ore more) of the following areas. In the event of cross-track expertise, please select the one you align to the most. Our interview process will be catered to verifying the chosen expertise area. Expertise Area 1 - Agentic system building Focus: Build systems that autonomously propose, execute, and verify scientific hypotheses over long time horizons. - Create and analyze long-running auto-research systems that propose and verify hypotheses - Design planning frameworks for agentic systems operating over long, sparse feedback loops - Design memory architectures that allow agents to build and retrieve

Join Our Talent Community Cambridge, MA USA; San Francisco, CA USA If you don't see a current role that matches your background but want to be considered for future opportunities at Lila, join our talent community here. About LILA Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply. We're All In Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy . A Note to Agencies Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited

Manager / Senior Manager, Product Marketing, Physical Science Cambridge, MA USA Your Impact at LILA We are seeking a Product Marketing Manager, Physical Sciences to lead go-to-market for Lila's AI-driven materials and chemistry platform. You will operate at the convergence of: - Physical science domains: catalysts, sorbents, coatings, LNPs, quantum and extreme-environment materials - Autonomous experimentation: flow chemistry ecosystems, high-throughput electrocatalysis, advanced characterization workcells - AI & modeling: property prediction, design spaces, Bayesian optimization, LLM-augmented optimization Your mission is to translate this tech stack into clear narratives, compelling launches, and credible evidence that resonate with: - Industrial R&D and technology leaders in energy, chemicals, and manufacturing - Sustainability and advanced materials teams - Strategic partners, national labs, and federal programs What You'll Be Building Go-To-Market Strategy & Launch - Define and execute GTM plans for new physical science capabilities (e.g., catalyst discovery campaigns, LNP property prediction, flow-reactor-based optimization, sorbents and coatings workflows), translating technical milestones into compelling market moments with clear offers, timelines, and success metrics. - Translate PS product milestones (new AISF demos, CLUE campaign results, partner-ready vignettes) into launch-ready packages, including positioning, messaging, collateral, and enablement assets. - Align launches with priority commercial motions in physical sciences (Accelerated By Lila, Lila Superscientists, joint development, and agentic science offerings) to maximize adoption and impact. Messaging & Positioning - Craft crisp, value-based messaging that communicates how Lila's platform accelerates: - Catalyst and materials discovery for green hydrogen and electrochemistry - LNP design and advanced materials development for transport and separations

Director / Senior Director, Product, Physical Sciences Cambridge, MA USA Your Impact at LILA Lila Sciences is hiring a Director, Product, Physical Sciences: a strategic, cross-functional product leader who shapes the vision, roadmap, and execution for platforms that accelerate scientific discovery and product development. Reporting to the Head of Physical Science Product, you will lead product strategy and delivery across capabilities at the intersection of physical science, simulation and physics-based modeling, lab automation, data and ML, and scientific intelligence. This role requires strong leadership, crisp prioritization, and the ability to translate complex technical and scientific work into clear product direction and measurable outcomes for internal teams, partners, and customers. You will be deeply customer-facing, serving as a trusted technical and product voice with prospects and partners, and shaping proposals, driving commercial conversations, and closing deals that bring Lila's Physical Sciences platform to market. What You'll Be Building - Set the long-term product vision, roadmap, and portfolio priorities for Lila's Physical Sciences portfolio. - Define product strategy and target product profiles (TPPs) for physical-science workflows: materials design, formulation, characterization, reliability, scale-up. - Drive product execution from concept to launch across physical sciences, simulation, automation, data engineering, and ML. - Represent product to executives, scientific leaders, partners, and customers as the senior external voice for the domain. - Own commercial outcomes end-to-end: opportunity shaping, proposal development, deal closure, and revenue for the domain. - Define success metrics and milestones (technical, product, commercial) and report progress clearly to leadership. What You'll Need to

Principal, Machine Learning Engineer San Francisco, CA USA Your Impact at LILA Lila is building a platform where AI and automation co-evolve to solve the hardest problems in medicine. Within Life Science AI (LSAI), ML engineers build and operate the systems that turn generative models and reasoning frameworks into production capabilities powering automated scientific discovery across Lila's life science domains. We are seeking a Principal ML Engineer to design, build, and scale the ML infrastructure behind models spanning biological sequence design, molecular structure prediction, antibody engineering, and multimodal scientific reasoning. You will own critical systems end to end, from training pipelines and distributed compute to model deployment and integration into Lila's closed-loop discovery engine. This is a high-impact IC role for someone who operates at the intersection of ML systems engineering and life science applications. You will shape the technical direction for how ML models are trained, evaluated, and deployed at scale, collaborate closely with AI scientists and experimental researchers to close the computational-experimental loop, and drive Lila's ML infrastructure toward the next generation of capabilities. What You'll Be Building - Design, build, and optimize large-scale training pipelines for generative models on biological and chemical data, including distributed training across GPU clusters - Own production ML systems end to end: model deployment, serving infrastructure, monitoring, and reliability for models used in Lila's scientific workflows - Architect ML infrastructure that supports rapid iteration across sequence design, structure prediction, and multimodal scientific reasoning workloads - Drive the engineering side of Lila's "Lab-in-the-Loop"

Director / Senior Director, New Product Planning, Life Sciences Cambridge, MA USA Your Impact at LILA Lila Sciences is hiring a Director / Senior Director, New Product Planning to help shape Lila Origins, our company and asset creation arm which partners to translate scientific vision into molecules, materials, and real-world ventures. As a member of a small, highly cross-functional team, you will bring the commercial voice to life sciences opportunities at the earliest stages, assessing where Lila's platform can produce differentiated assets and shaping how those opportunities become ventures, partnerships, or programs. You will spend your time at the interface of science, market, and deal structure. You will match therapeutic modalities to disease areas based on biological fit, competitive landscape, and commercial viability. You will build quantitative views of opportunities (market sizing, patient population modeling, deal economics) and translate them into recommendations for Origins and Lila leadership. You will pressure-test ideas with external operators, investors, and partners, and use what you learn to sharpen Lila's Origins thesis. This role suits someone who has run new product planning, asset strategy, or commercial assessment work inside a pharma or biotech organization, lives close to industry trends, and is drawn to a builder environment where the asset list is being defined in real time. You will work closely with the VP, Head of Lila Origins, and sit within Corporate Development. The work is high ambiguity, high leverage, and deliberately cross-disciplinary. What You'll Be Building - Source and evaluate new life sciences opportunities for

Staff Forward Deployed Engineer, Life Sciences Cambridge, MA USA Your Impact at LILA We're seeking extraordinarily talented Forward Deployed Engineers across Engineer, Senior Engineer, and Lead Engineer levels to join our growing team. Our FDEs are high-performing generalists with a broad set of skills, in addition to depth in one or more focus areas. As an FDE, you'll embed directly with our internal biotech and science teams as well as external customers, living their problems and rapidly building solutions that transform their research capabilities. You'll leverage our AI and software platform tools while developing bespoke features that address each customer's unique challenges. This isn't traditional software development-it's high-velocity, AI-fueled, high-impact engineering where you'll ship production code in days, not months. What You'll Be Building - Developing, wrapping, and adapting domain-specific tools for molecular modeling, data analysis, process optimization, molecular modeling, and more - Deploying custom, agentic scientific workflows that integrate with industrial instruments (PLCs, control software) and data systems (ERP, MES, SCADA) - Building real-time data pipelines that transform messy scientific data into actionable insights - Creating intuitive interfaces that make complex AI/ML capabilities accessible to scientists - Architecting solutions that scale from proof-of-concept to enterprise-wide deployment What You'll Need to Succeed - Background in biology, molecular science, or related scientific field - Outstanding communication skills-you'll interface directly with both executives and the manufacturing line - Experience with data engineering, ETL pipelines, and working with complex/messy datasets - Strong full-stack development skills with the ability to work across backend, frontend,

Senior Research Associate/Associate Scientist, Platform Scientist Cambridge, MA USA Your Impact at LILA As a Senior Research Associate / Scientist on the Platform Science team within Lila's Autonomous Science Platform, your work will directly contribute to building Lila's next-generation, AI-driven research capabilities. You will have the opportunity to pioneer novel automated instruments centered around advanced processing and characterization of solid state materials - at the critical intersection of hardware, software, and scientific inquiry. This role is a unique blend of hands-on engineering and scientific investigation, where you will prototype, automate, and validate the platforms that will define the lab of the future. You will operate across a broad set of disciplines, working closely with the vacuum synthesis, platform science, and characterization teams to build tools that dramatically accelerate the pace of scientific discovery and support active research campaigns across multiple initiatives. What You'll Be Building - Design, construct, and integrate novel automated experimental platforms with a material emphasis on solid state synthesis and novel processing methods, working in close collaboration with the vacuum synthesis, platform, and characterization teams to align on system requirements and share technical knowledge. - Work hands-on to integrate hardware components, including optics, robotics, and sensors, into a cohesive, automated workflow. - Develop end-to-end software stacks from instrument control to data stewardship and integration with downstream models. - Analyze instrument data to validate system performance, troubleshoot issues, and support research initiatives designed to establish and expand the capabilities of new platforms. - Collect, document, and interpret experimental

Staff / Principal Research Engineer, AI Safety, Technical Mitigations Cambridge, MA USA; London, UK; San Francisco, CA USA Your Impact at LILA We're building a talent-dense, high-agency AI safety team at Lila that will engage all core teams within the organization (science, model training, lab integration, etc.), to prepare for risks from scientific superintelligence. The initial focus of this team will be to build and implement a bespoke safety strategy for Lila, tailored to its specific goals and deployment strategies. This will involve technical safety strategy development, broader ecosystem engagement, safety-focused evaluations, safety systems to mitigate risks, and a safety research agenda that explores longer-term needs such as oversight of superintelligent scientific systems. We're seeking a Technical Mitigations Lead, to lead the build out of safety systems at Lila for the safe deployment of our scientific capabilities to the world. Given the novelty of Lila's workflows, integrating frontier-class language models with narrow scientific tools and lab-based automation, this role will require the design and deployment of technical safeguards beyond the current state-of-the-art. We expect the person in this role to start off the initial mitigations build-out, and then slowly build a team to support this function. What You'll Be Building - Set the build and research strategy for Lila's safety systems, across scientific data analysis and generation pipelines, safety post-training, refusal classifiers, automated safety-testing / red-teaming systems, and monitoring systems. - Conduct initial safeguards experimentation and buildout for Lila's specific scientific needs, and subsequently lead a small team to execute

Scientist, Epitaxial Thin Film Synthesis Cambridge, MA USA Your Impact at LILA As an epitaxial thin film scientist on the Materials Science team at Lila Sciences, you will serve as the lead for synthesis of high-quality epitaxial thin films, contributing to the discovery of novel quantum materials with emergent electronic and magnetic properties. Your domain expertise at the intersection of materials growth, structural characterization, and electronic transport will translate into the method design and automated workflow to enable high throughput experimentation that Lila's autonomous science platform learns from. This work contributes to Lila's materials science programs focused on the predictive design of novel material families and compounds with novel functional properties. You will design growth and characterization protocols that shape how the platform interrogates new material systems, and your experimental outputs feed directly into the next round of campaigns. You will partner with experimentalists, systems engineers, and machine learning scientists, providing the functional-properties knowledge that keeps closed-loop campaigns scientifically grounded and accelerating toward next-generation materials systems. What You'll Be Building - Grow single-crystal epitaxial thin films and heterostructures using epitaxial deposition methods (sputtering, pulsed-laser deposition, molecular beam epitaxy). - Optimize deposition conditions (substrate temperature, flux ratios, growth rate) to achieve atomically sharp interfaces and target crystal phases. - Analyze XRD and AFM data. - Design, fabricate, and measure electronic transport devices, including temperature-dependent resistivity, Hall effect, and magnetoresistance. - Analyze magneto-transport data to extract physical parameters and identify emergent ground states. - Maintain deposition and characterization equipment; troubleshoot hardware and

Manager / Senior Manager, Product Marketing, Life Science Cambridge, MA USA Your Impact at LILA We are seeking a strategic Product Marketing Manager (Life Science) to own go-to-market for Lila's life science product portfolio. You'll translate complex, closed-loop AI and lab capabilities-such as mRNA design, DNA construct optimization, and AI-driven medicinal chemistry-into clear, credible stories and compelling commercial offerings for: - Biopharma and advanced therapy companies - R&D and CMC leaders - Data science / AI teams and scientific IT In collaboration with the Life Science Product team, you will shape RNA and DNA design technology tiles, hit-to-lead and lead optimization offerings, and early commercial pilots. Your work will define positioning, launch plans, and evidence strategies that move prospects from curiosity to committed programs. You'll articulate value, build differentiated narratives, and enable cross-functional execution across product, sales, and customer success to accelerate adoption and drive measurable business impact. What You'll Be Building Messaging & Positioning - Define and continuously refine product narratives for Lila's life science capabilities (RNA/mRNA design, DNA constructs, protein and small molecule optimization, AISF-powered workflows). - Tailor messaging to specific personas (Heads of R&D, Therapeutic Area leaders, CMC, translational and bioinformatics leads, Scientific IT) and use cases (hit-to-lead, mRNA design, in vivo CAR-T data stories). - Ensure all external materials reflect Lila's master narrative on scientific superintelligence, safety, and multi-domain learning. Go-To-Market Strategy & Launch - Lead end-to-end GTM for new life science capabilities: from beta/pilot framing through general availability and expansion. - Partner with Product, Commercial,

Principal ML Research Engineer San Francisco, CA USA Your Impact at LILA Lila is building a platform where AI and automation co-evolve to solve the hardest problems in science. Within Life Science AI (LSAI), we are launching a new AI for Cell Biology team to develop autonomous-science capabilities for cellular and tissue biology, spanning single-cell omics, perturbation biology, spatial profiling, imaging, genetics, and multi-modal experimental data; that integrate deep biological expertise with foundation modeling and agentic systems. We are seeking a Principal ML Research Engineer to be the founding engineering leader on this team . This is a 0→1 hands-on role. You will build and operate the engineering platform : domain data, domain-specific models, shared specialist-model serving and inference, agentic infrastructure, and the evaluation harness that the team's research programs run on, and that integrates cell-biology research with Lila's central autonomous-science platform: it's core-model, agentic-systems, and experimental-automation infrastructure that closes the loop between AI reasoning and the lab. You will work closely with Lila's central AI Platform, Data Platform, and autonomous-lab engineering teams to leverage and extend core Lila infrastructure rather than rebuild it , and you will co-develop the technical direction of the team with the VP of AI for Cell Biology and its ML Scientists as you build. Cell- and tissue-scale biology sits at an open frontier of AI for science. The field has produced strong specialist models across sub-domains: single-cell foundation models, molecular structural prediction, perturbation response, cellular imaging, pathway and ligand-receptor inference - but the engineering

Director, Federal Strategy and Capture, Government Partnerships Cambridge, MA USA Your Impact at LILA Lila Sciences is looking for a Director of Federal Strategy & Capture to convert senior agency relationships and deep policy fluency into real government partnerships and funding wins. This role sits within our Government Partnerships organization and operates at the front end of capture - shaping the competitive environment before opportunities are formally announced, reading where the federal funding landscape is heading, and opening doors that demand genuine scientific and policy credibility. This is not a policy role. It's a capture role that requires someone with unusually deep federal experience. What You'll Be Building Named Account Ownership - Build, manage, and advance senior relationships at DOE, ARPA-E, NIH, and adjacent US mission agencies. You own the health, depth, and trajectory of those relationships over time. Opportunity Shaping - Engage agencies early enough to influence how funding opportunities are scoped and structured before they become RFPs, ensuring alignment with Lila's strategic roadmap. Cross-Agency Narrative Development - Partner with the Head of Government Partnerships to connect Lila's portfolio to national science priorities and build a prioritized federal pipeline. Institution Building - Help stand up Lila's federal capture function, including how we track relationships, manage pipeline, and engage agencies systematically over time. What You'll Need to Succeed - Senior US federal experience at the intersection of science, policy, and strategy - agency, NSC, interagency, or equivalent background - Scientific fluency in life sciences, biotechnology, or adjacent domains - A

ML Scientist I / II, Foundation Models for Life Sciences San Francisco, CA USA Your Impact at Lila Lila is building a platform where AI and automation co-evolve to solve the hardest problems in medicine. Within Life Science AI (LSAI), the Foundation Models team researches and develops large-scale generative models and reasoning frameworks that power automated scientific discovery across Lila's life science domains. We are seeking a Scientist I or II to join this team as a contributor to foundation model research at the intersection of machine learning and life science data. You will work on generative models spanning biological sequences, molecular structures, and multimodal experimental data, contributing to problem formulation, model design, training, evaluation, and integration into Lila's closed-loop discovery engine. This is an IC role for someone building deep expertise in generative AI applied to biology. You will own research sub-problems end to end, collaborate closely with experimental scientists to close the computational-experimental loop, and contribute to Lila's presence in the broader scientific community. What You'll Be Building - Contribute to research on foundation models for life science applications, including biological sequence design, structure prediction, and multimodal scientific reasoning - Design, train, and evaluate generative models on biological and chemical data, incorporating domain-specific constraints and priors - Be part of the end-to-end ML process within Lila's "Lab-in-the-Loop" lifecycle: support data generation strategy, build pipeline models, and help design feedback loops where experimental results improve model performance - Translate biological questions into well-defined ML problems and interpret model outputs

Senior / Principal ML Scientist, Foundation Models for Life Sciences San Francisco, CA USA Your Impact at LILA Lila is building a platform where AI and automation co-evolve to solve the hardest problems in medicine. Within Life Science AI (LSAI), the Foundation Models team researches and develops large-scale generative models and reasoning frameworks that power automated scientific discovery across Lila's life science domains. We are seeking a Principal or Senior Principal Scientist to join this team as a core contributor. You will define and drive research at the intersection of state-of-the-art machine learning and life science data, spanning biological sequences, molecular structures, and multimodal experimental data. As part of a dynamic team, you will design and implement foundational models end to end, from problem formulation and architecture through training at scale, evaluation, and integration into Lila's closed-loop discovery engine. This is a high-impact IC role for someone who operates at the frontier of generative AI applied to biology. You will shape the technical agenda for foundation model research, collaborate closely with experimental scientists to close the computational-experimental loop, and represent Lila's work to the broader scientific community. What You'll Be Building - Drive research on foundation models for life science applications, including but not limited to biological sequence design, structure prediction, and multimodal scientific reasoning - Design, train, and evaluate large-scale generative models on biological and chemical data, integrating domain-specific constraints and priors - Contribute to the end-to-end ML process within Lila's "Lab-in-the-Loop" lifecycle: steer data generation strategy, build pipeline

Senior / Principal Scientist, AI for Protein Engineering San Francisco, CA USA Your Impact at LILA Lila is building a platform where AI and automation co-evolve to solve the hardest problems in medicine. Within Life Sciences AI (LSAI), the AI for Protein Engineering team develops and uses the generative and predictive models that drive Lila's biomolecule design programs from in silico hypothesis to wet-lab validated lead. We are seeking a Senior or Principal Scientist to join this team as a senior IC focused on antibody design and engineering. You will develop and execute the methods and workflows that ensure successful completion of antibody campaigns. Scope may expand to additional modalities such as enzymes and peptides as needs evolve. This role sits at the bilingual edge of ML and biology. You will own biological understanding of campaign needs and partner closely with the Life Science Research team to design and validate computational predictions in the lab. You will shape the technical agenda for AI protein engineering at Lila and represent that work both internally and to the broader research community. What You'll Be Building - Develop and own protein design and engineering workflows for antibody campaigns, including de novo design, affinity maturation, and developability optimization - Execute design workflows end-to-end for active campaigns and deliver wet-lab-validated leads against program milestones - Translate campaign requirements - epitope selection, affinity targets, biophysical constraints, and developability criteria - into well-defined ML problems and design specifications - Adapt and extend state-of-the-art AI methods (generative models,