Synthetic Sciences jobs

Engineer - Drug Substance Synthetic Molecule Design and Development US, Indianapolis IN posted: Posted 4 Days Ago

Senior Member of Technical Staff, Synthetic Data Toronto | Remote | New York | London | Paris | Montreal Who are we? Our mission is to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what's best for our customers. Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products. Join us on our mission and shape the future! Why this role? As a Senior Machine Learning Engineer specializing in synthetic data, you will play a pivotal role in developing the synthetic data pipeline that is crucial to Cohere's advanced language models. Your responsibilities will encompass the end-to-end management of synthetic data, including maintaining and optimizing the synthetic data pipeline, data analysis and generation, as well as conducting data ablations and model evaluation to gauge data quality. You will work with diverse web data and code data and transform them

Research Scientist, Materials Synthesis Menlo Park, California, United States About Periodic Labs The most important scientific discoveries of our time won't happen in a traditional lab. We're an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what's scientifically possible. About the Role Join a world-class team of scientists and engineers pushing the boundaries of materials research in a groundbreaking lab where AI and automation unlock discoveries at unprecedented speed and scale. As a Research Scientist within the Periodic Labs experimental effort, you bring computational predictions into reality through solid state materials chemistry. In this role, you will both develop new materials synthesis approaches and be part of the team developing autonomous discovery loops. What You'll Do - Develop strategies to synthesize novel solid state materials - Reveal and control the atomic structure of these materials through advanced characterization - Collaborate with the AI team in the development of predictive tools and analysis techniques grounded in chemistry and materials science - Collaborate with the engineering team to design and test new automated laboratory hardware for synthesis and characterization You Will Thrive in This Role If You Have - PhD in chemistry, physics, or materials science, with 5+ years of hands-on experience - Proficiency with a diverse range of synthesis methods within solid

Research Synthesis Chemist Milton Park, England Your work will change lives. Including your own. The Impact You'll Make We are growing our chemistry team at Recursion and are seeking a Research Synthetic Chemist to join our Automated Chemistry group. We are looking for an individual that thrives in a dynamic and collaborative team environment and successfully adopts new technologies and workflows to accelerate drug discovery. You will independently convert synthesis requests into structured experimental plans for our state-of-the-art Chemistry Automation platform. You will collaborate with other scientists and automation specialists with our chemistry team to meet project deadlines by providing hands-on experimental support and take ownership of your experimental work to deliver compounds and reaction data. With structured training and drawing on previous experience of lab automation or methodology development, you will develop deep familiarity with the Chemistry Automation Platform and workflow software, and be able to propose, develop and translate new methodologies onto the automated platform in collaboration with senior chemists and automation engineers. In this role, you will: Execute synthetic routes by seamlessly integrating traditional laboratory techniques with our automated chemistry platforms to deliver high-quality compounds independently for drug discovery projects. Translate synthetic methods to the automation platform utilising critical thinking and your technical knowledge of chemical reactivity and methodology development. Learn how to diagnose and resolve chemical or procedural issues within our automated workflows seeking assistance from automation specialists where needed. Collaborate with teams at the interface of automated chemistry, medicinal chemistry, software and hardware engineering to

Director, Discovery Chemistry Cambridge, MA USA Your Impact at LILA The Director, Discovery Chemistry will lead the design, synthesis, and optimization of small molecules across Lila's discovery platform, with a primary focus on organic synthesis, molecular design, and scalable chemistry execution . This leader will build and scale a world-class molecular chemistry program that translates AI-generated molecular hypotheses into high-quality, synthetically tractable, and functionally validated chemical matter. Working closely with Lila's AI, automation, computational, biology, and platform teams, this role will establish the chemistry infrastructure required to rapidly progress novel molecules from concept to validated candidates across a broad range of discovery efforts. The Director will drive synthetic strategy, route design, analog generation, molecular property optimization, and chemistry-enabled innovation, while enabling seamless integration with robotic synthesis and platform-based experimentation. This leader will play a central role in shaping Lila's molecular discovery engine by combining deep expertise in synthetic organic chemistry, molecular design, and data-enabled experimentation to accelerate the discovery of high-value molecules for therapeutic and broader platform applications. What You'll Be Building - Drive discovery chemistry strategy across discovery programs, with strong emphasis on small molecule design, synthetic innovation, analog generation, and optimization of chemical matter. - Lead the design and execution of synthetic routes for novel small molecules, emphasizing speed, robustness, scalability, and compatibility with automated synthesis platforms. - Develop and implement efficient workflows for molecular design, compound prioritization, analog generation, and iterative design-make-test cycles in collaboration with AI and computational teams. - Partner closely with automation and platform

AI Research Scientist —Generative AI for Materials Discovery Redmond, WA; Pasadena, CA Meta's Reality Labs Research (RL-R) brings together a team of researchers, developers, and engineers to create the future of Mixed Reality (MR), Augmented Reality (AR), and Wearable Artificial Intelligence (AI). The Materials and Systems Innovation (MSI) group within Reality Labs Research creates and accelerates breakthrough materials and device technologies that unblock the path to low-cost, all-day wearable AR devices and advanced sensing and actuating systems for robotics. We identify key technology gaps requiring step-change innovation, build AI-driven autonomous discovery pipelines to compress development timelines, leverage external partners to accelerate research, and deliver high-quality technology solutions through cross-functional, high-performing teams. In this role, you will pioneer the application of generative AI to design novel compounds and molecular crystals, directly accelerating the discovery of next-generation materials for AR/VR devices and advanced robotic systems. Working at the frontier of deep generative modeling, computational chemistry, and agentic AI, you will develop and deploy state-of-the-art models - including diffusion models, flow matching, and transformer-based architectures - that predict and generate stable crystal structures and molecular candidates with target properties. Your work will be tightly integrated into our AI-driven autonomous discovery platform, collaborating with computational chemists and AI agent scientists to close the loop from molecular design to experimental validation. Together, we are going to build advanced prototypes, technologies, and toolsets that can advance how people interact with their surroundings. We invite you to join us as we work to bring these technologies from

Scientist II, Cheminformatics Cambridge, MA The Opportunity: Relay Therapeutics is seeking a highly motivated Scientist to join our Drug Discovery team in a unique hybrid role that integrates synthetic chemistry with cheminformatics. This position is ideal for a scientist who enjoys working at the interface of experimental and computational disciplines and is excited to help shape how data-driven chemistry is done in a modern biotech environment. Your Role: - Maintain and support tools used in compound registration, lab operations and data ingestion from assays, as well as broader data and software access workflows - Design and execute synthetic chemistry workflows, with a focus on high-throughput or parallel synthesis to support medicinal chemistry programs - Contribute to the design, enumeration, and prioritization of compound libraries using cheminformatics tools - Collaborate closely with computational chemists, data scientists, and medicinal chemists to guide compound design using data-driven insights - Analyze and interpret experimental data to inform structure-activity relationships (SAR) and compound optimization - Help develop and refine internal workflows that integrate synthetic chemistry with computational approaches - Maintain clear documentation and communicate results effectively across multidisciplinary teams Your Background: - Ph.D. or M.S. in Organic Chemistry or a related field, with 2-5 years of relevant industry experience preferred - Demonstrated experience in synthetic organic chemistry - Familiarity with cheminformatics tools and concepts (e.g., molecular representations, library design, property prediction) - Experience with scripting or data analysis tools (e.g., Python, RDKit) - Strong problem-solving skills and the ability to work both independently and collaboratively

Synthetic Flight Instructor Gurugram posted: Posted 2 Days Ago

Senior Software Engineer, Perception ML Data Mountain View, California (HQ) About the Role We're a team of high-output generalists where ML and systems engineering converge to push autonomy performance forward. As a Perception ML Data Engineer, you'll bridge machine learning innovation and autonomy infrastructure to ensure our models learn from the most relevant, diverse, and high-quality data. Your work will directly impact how autonomous systems understand rare scenarios, adapt to global geographies, and scale safely. Design and advance systems that : - Leverage VLMs to curate geographically diverse datasets matching real-world driving distributions - Develop high fidelity synthetic data frameworks across sensor modalities - Optimize ML-powered validation of data quality and model readiness Tailor Your Impact : - High-Output Generalist: Work across autonomy, infrastructure, databases, simulation, and ML development, gaining domain knowledge in Robotics and ML. - Robotics Expert: Build state of the art solutions for data discovery, auto-labeling, and synthetic generation/reconstruction in close collaboration with Infrastructure and Autonomy. About the work You'll solve autonomy's hardest data challenges through applied ML and systems rigor: - Architect hybrid systems combining deep learning and classical algorithms for scalable data curation and annotation. - Design frameworks to quantify synthetic data's real-world fidelity and improve synthetic data rendering quality. - Build tools that automatically surface data gaps impacting perception model performance. - Collaborate with autonomy engineers to turn raw sensor streams into targeted training priorities - addressing critical gaps that limit perception and autonomy performance About You - BS in Computer Science, Robotics, Statistics,

Synthetic Flight Instructor (SFI) Singapore Area posted: Posted 30 Days Ago

CompChem Research Scientist (Free Energy Methods) - Sr. - Principal NYC or SF Bay Area, NYC, or SF Bay Area, California or NY, United States About Genesis Molecular AI Genesis Molecular AI unifies cutting edge molecular machine learning with rigorous physics to discover novel small molecule therapies for severe diseases. Our molecular AI platform, GEMS, combines generative models and high throughput molecular simulation to search chemical space and prioritize compounds with unprecedented speed and accuracy. We are bringing together a world-class computational team to build out the industry's fastest and most accurate small molecule property predictions, by combining the power of machine learning and physics-based methods. About the Team Our computational chemistry team partners with ML researchers, medicinal chemists, and biologists to turn our computational models into real drug candidates for our internal pipeline and our pharma collaborators. You will join a team led by experienced drug hunters and method developers across statistical mechanics, free energy methods, and computer aided drug design. About the Role We are looking for a binding free energy specialist, who is comfortable both with the theory necessary to propose new methodological ideas and with coding necessary to implement them. This individual will advance free energy methods across our platform and own their delivery. You will be the person our teams turn to when they need physics based ranking of tight binders, especially in potency regimes where current models start to flatten out. Your work will directly shape which compounds we make, which ones move forward,

Synthetics Principal Product Quality Leader 2 Locations posted: Posted 7 Days Ago

Foundation and generative models for biomolecules Berlin, Germany or Palo Alto, CA or Zurich, Switzerland At Inceptive, you will drive forward development that could help billions of people. To accomplish this, you will be part of a collaborative, antedisciplinary team building our biological software. The design space of biomolecules is unimaginably vast - far beyond what can be explored experimentally. Yet within this space lie molecules with properties essential for new medicines. Our machine learning models learn to design therapeutic biomolecules with specific, desirable functions. We advance the state of the art in molecular design by training large-scale foundation models and developing cutting edge generative approaches. The models learn from diverse heterogeneous datasets and are refined through focused fine-tuning and feedback from experiments. Key to progress is a team that combines exceptional machine learning expertise with thorough domain understanding. You will collaborate closely with other machine learning researchers and engineers, as well as computational and experimental biologists, to advance these models and translate their capabilities into real therapeutic designs. Your Mission, should you choose to accept it - Embody our vision of an antedisciplinary environment and embrace learning about areas outside of your traditional area of expertise - Develop, implement, train, and iteratively improve state-of-the-art models for biomolecule design - Analyze, visualize, and communicate results to support team efforts in improving models and data - Create, deploy, and refine tools for efficient, reliable machine learning experimentation and production - Work with biologists to collect data for the training and evaluation

Synthetic Flight Instructors/Examiner Burgess Hill, United Kingdom posted: Posted 30+ Days Ago

Sr. QA Associate - Commercial Synthetics Geel, Antwerp, Belgium posted: Posted Today

Research Scientist (Engineering) Remote fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products. As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on. About this role: You are an ML Researcher who has a broad view of the generative media space and an update-to-date awareness of new methods in the space. You can spot products and features that are missing in the current market and work backwards to develop new methods to solve customers problems. Sometimes your work will require entirely novel training or architecture developments. While other times it will require fine-tuning pre-existing models with novel datasets. You are able to consider the expected return on investment of different approaches, and more excited about using research to develop novel products, then research for research's sake. Tech: - You will have access to our massive GPU cluster for training and inference - Some core technologies we use include Python, torch, diffusers, and the fal Python SDK - You'll work alongside a team dedicated to quickly iterating on and

AI Research Scientist — Agentic AI for Materials Discovery Redmond, WA; Pasadena, CA This role sits within Meta's Reality Labs Research, in the Material and Systems Innovation team, which develops advanced materials for two of Meta's most ambitious hardware frontiers: lightweight, all-day wearable AR glasses and next-generation sensing and actuating materials for robotics. The AI Specialist will design and build LLM-orchestrated multi-agent systems that autonomously drive materials discovery pipelines - from computational screening and simulation through synthesis and characterization - across both domains. By closing this loop with agentic AI, we aim to compress discovery timelines from years to weeks, directly accelerating Meta's ability to ship breakthrough AR/VR and robotics hardware. This position bridges two of Meta's highest-priority investment areas - frontier AI and the physical systems underpinning the metaverse and embodied intelligence - and will contribute both production systems and published research at top-tier venues. Responsibilities: - Design, implement, and optimize LLM-orchestrated multi-agent systems for autonomous materials discovery pipelines - Build specialized AI sub-agents that operate within a closed-loop discovery framework - Integrate agentic AI workflows with computational chemistry tools (DFT, MD, Monte Carlo) and HPC infrastructure - Develop and fine-tune retrieval-augmented generation (RAG) systems over scientific literature corpora for real-time knowledge synthesis - Collaborate with materials scientists, computational chemists, and ML researchers to translate domain workflows into autonomous agent architectures - Evaluate and benchmark agent performance on materials discovery tasks - measuring accuracy, throughput, and synthetic viability of generated candidates - Contribute to open-source tooling and publish research

Asia Synthetic Prime Brokerage Trader - Director HONG KONG, Hong Kong

Synthetic Data Generation and User Simulation PhD Research Intern — Fall 2026 US, CA, Remote posted: Posted 16 Days Ago

Intern, Protein Design Lausanne / Hybrid / Remote | Hybrid | Remote Adaptyv is building an automated lab thats let AI agents run biology experiments. We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world. We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today. Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development. We're growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation. RESPONSIBILITIES - Run and benchmark open-source protein design methods on real Adaptyv targets, validated against experimental data from our wet lab. - Design binders for internal R&D campaigns, and track experimental performance across success rate, hit rate, kinetics, and developability. - Build computational tooling around the design pipeline: structure prediction, filtering, and ranking, to triage large design pools

Data Scientist - Synthetic Data and ML Evaluations - Special Projects Cupertino, United States of America Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or experience we deliver is the result of us making each other's ideas stronger. The diversity of our people and their thinking inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something. The Special Projects team at Apple is developing novel user-facing conversational features that leverage the multimodal capabilities of state-of-the-art foundation models. A key component of this process is the ability to produce complex simulated scenario data, in order to train and evaluate agentic AI models. We are looking for a skilled Data Scientist to work closely with our Simulation and Machine Learning Evaluations teams to generate large synthetic datasets, analyze the gap between simulated and real data, and evaluate and fine-tune agentic AI model performance at various tasks. A successful candidate is experienced in managing large, multi-modal datasets, in translating subjective product requirements into objective criteria, and has strong statistical analysis skills. Work closely with ML Engineers to understand model evaluation needs Work closely with the Simulation team to design and generate large, multi-modal datasets for model evaluation Analyze the gap between simulated and real data Collaborate with the Simulation team to prioritize and

Applied Sciences Manager , Ads Brand Safety and Suitability London, England, GBR Amazon Ads Brand Safety & Suitability protects advertisers from exposure to unsafe, unsuitable, or policy-violating content across web, mobile app, CTV, and audio advertising inventory. Our mission is to ensure that every ad impression delivered through Amazon's demand-side platform appears adjacent to content that meets advertiser trust expectations while giving brands granular controls to define suitability on their own terms. We operate at the intersection of advertiser trust, publisher quality, and supply integrity. AI is fundamentally changing the content landscape. Content is now generated at unprecedented scale - faster, cheaper, and increasingly sophisticated. Low-quality, deceptive, AI-generated, and synthetic content evolves in real time, constantly adapting to evade detection. The volume and velocity of new content entering the advertising system has outpaced traditional classification approaches. We are looking for an Applied Science Manager to lead the next generation of AI-powered Brand Safety and Content Classification systems designed to protect advertisers and elevate supply quality at internet scale. This is not a traditional classification problem. Your team will build systems that make millisecond-level decisions across billions of content signals while continuously adapting to emerging content risks driven by generative AI. You will own the science roadmap for LLM-powered classification and semantic understanding, real-time multimodal content evaluation, adversarial ML and adaptive model resilience, proactive risk intelligence and content risk hunting, AI-generated and synthetic content detection, and large-scale abusive content system identification and disruption. You will define how modern AI separates high-quality

Synthetic DNA Process Development Scientist Louisville, KY, United States Company Description: Eurofins Scientific is an international life sciences company, providing a unique range of analytical testing services to clients across multiple industries, to make life and our environment safer, healthier and more sustainable. From the food you eat, to the water you drink, to the medicines you rely on, Eurofins works with the biggest companies in the world to ensure the products they supply are safe, their ingredients are authentic and labelling is accurate. Eurofins is the global leader in food, environment, pharmaceutical and cosmetic product testing and in agroscience Contract Research Organisation services. Eurofins is one of the market leaders in certain testing and laboratory services for genomics, discovery pharmacology, forensics, advanced material sciences and in the support of clinical studies, as well as having an emerging global presence in Contract Development and Manufacturing Organisations. The Group also has a rapidly developing presence in highly specialised and molecular clinical diagnostic testing and in-vitro diagnostic products. In over just 30 years, Eurofins has grown from one laboratory in Nantes, France to 55,000 staff across a decentralised and entrepreneurial network of 900 laboratories in over 50 countries. Eurofins offers a portfolio of over 200,000 analytical methods to evaluate the safety, identity, composition, authenticity, origin, traceability and purity of biological substances and products. Job Description: Position Summary We are seeking a highly skilled and motivated Organic Chemist with expertise in oligonucleotide synthesis and purification to support process development and manufacturing. This role

Advisor — Synthetic Chemist / Peptide Therapeutics (Indianapolis) US, Indianapolis IN posted: Posted 21 Days Ago