Vector jobs

Senior Software Engineer, Applied AI Cambridge, MA USA; San Francisco, CA USA Your Impact at LILA We are seeking a Senior Software Engineer to join our Applied AI group and help build the next generation of our AI-driven scientific platform. In this role, you will design and optimize the backend systems, data pipelines, and AI integrations that power intelligent, data-driven applications. You'll work at the intersection of backend engineering and machine learning, ensuring our platform seamlessly scales and supports cutting-edge applied AI techniques such as Retrieval-Augmented Generation (RAG), agentic AI, and large language model (LLM) integration. This role is ideal for someone who thrives in bridging software engineering and applied AI-turning research into production-grade systems that drive real-world scientific discovery. If you are passionate about building performant, elegant systems that make AI useful and impactful, we would love to hear from you! What You'll Be Building - Applied AI Integration: Design and deploy backend services and data pipelines that directly support advanced AI applications, including LLMs, RAG, and agentic frameworks. - API & Service Development: Build high-performance APIs and microservices that enable seamless integration between AI models, scientific tools, and user-facing applications. - Data Pipeline Architecture: Architect and manage scalable pipelines capable of handling structured, unstructured, and vectorized data for AI/ML workloads. - Database & Knowledge Systems: Implement and optimize SQL, NoSQL, and vector databases to support low-latency AI retrieval and inference workloads. - Cloud & Infrastructure: Leverage AWS, Kubernetes, and infrastructure-as-code (Terraform/CloudFormation) to build robust, production-ready AI platforms. -

AI Lab - Machine Learning Engineer Sant Cugat del Valles, Barcelona, Spain

Principal AI Solution Architect, Data & AI Specialist Solutions Architect team Sydney, New South Wales, AUS Amazon Web Services (AWS) is leading the next phase of AI adoption and is seeking a hands-on AI Specialist Solution Architect (SSA). AWS Specialist Solutions Architects (SSAs) are technologists with deep domain-specific expertise, able to address advanced concepts and feature designs. As part of the AWS sales organization, SSAs work with customers who have complex challenges that require expert-level knowledge to solve. SSAs craft scalable, flexible, and resilient technical architectures that address those challenges. This might involve guiding customers as they refactor an application or design an entirely new cloud-based system. Specialist SAs play a critical role in capturing customer feedback, advocating for roadmap enhancements and anticipating customer requirements as they work backwards from their needs. As domain experts, SSAs also participate in field engagement and enablement, producing content such as whitepapers, blogs, and workshops for customers, partners, and the AWS Technical Field. This role focuses on converting AI ambition into programs that can be delivered, operated, and scaled in production environments. Key job responsibilities • The AI Specialist SA team builds technical relationships with customers of all sizes and operate as their trusted advisor, ensuring they get the most out of the cloud at every stage of their journey while adopting GenAI/ML and Agentic technologies across their organisation. • You'll manage the overall technical relationship between AWS and our customers, making recommendations on security, cost, performance, reliability and operational efficiency to accelerate their

Bachelor's Thesis „Geometry Database Creation for AI Model Training“ Graz, AT posted: Posted 30+ Days Ago

Agentic Data Specialist (Multiple Levels) Canada - Toronto; Ontario - Remote; British Columbia - Remote; Canada - Vancouver About the Role: We are seeking a technically adept and innovative Agentic Data Specialist to join our Forward Deployed Engineering Team. You will serve as the crucial link between our advanced AI agents and the wider enterprise technology landscape. Your primary responsibility will be to design, build, and manage the data and integrations that enable our Agentforce agents to take meaningful, autonomous actions across various business systems. You will not only connect agents to systems but also orchestrate a collaborative network of specialized AI agents, ensuring they work together seamlessly to solve complex business problems. If you are an expert in connecting disparate systems and are excited by the challenge of enabling AI to act upon its insights, this role is for you. As an Agentic Data Specialist , you will serve as the crucial link between our advanced AI agents and the wider enterprise technology landscape. Your primary responsibilities will focus on designing, building, and managing the data, systems, and logic that enable our Agentforce solutions to take meaningful, autonomous actions. Your Impact: Data Flow and Transformation: Manage the real-time flow of data to and from the AI agent. Implement necessary data transformations to ensure compatibility between different system formats and schemas. Architect AI Grounding Systems: Design, build, and maintain cutting-edge AI data integration technologies, including RAG (Retrieval-Augmented Generation), vector databases, search indexes, and knowledge bases, specifically to ground Agentforce solutions

Senior Deep Learning Engineering - Autonomous Vehicles 2 Locations posted: Posted 29 Days Ago

Senior AI Engineer Singapore Role Overview This role will be the technical foundation builder for the company's AI transformation. You will design and build the company-wide knowledge infrastructure and context layer that powers future AI applications. This is a highly hands-on role requiring strong backend engineering capability, LLM application experience, product sense, and the ability to operate independently in a fast-moving, ambiguous environment. Role Overview This role will be the technical foundation builder for the company's AI transformation. You will design and build the company-wide knowledge infrastructure and context layer that powers future AI applications. This is a highly hands-on role requiring strong backend engineering capability, LLM application experience, product sense, and the ability to operate independently in a fast-moving, ambiguous environment. Key Responsibilities - Design and build the company-wide AI knowledge infrastructure, including company wiki, internal knowledge base, retrieval layer, and context management system. - Develop scalable LLM application architecture, including RAG pipelines, vector database integration, prompt workflows, API services, monitoring, and deployment. - Own the end-to-end technical delivery of internal AI tools, from backend architecture and basic frontend integration to deployment, testing, and monitoring. - Work closely with business, brand, PR, IR, and leadership stakeholders to translate ambiguous business needs into practical AI systems and technical roadmaps. - Optimize system performance, including token efficiency, latency, caching strategy, retrieval quality, data architecture, and model inference flow. - Evaluate and integrate AI coding tools, LLM frameworks, vector databases, and third-party APIs to improve development efficiency and product quality. - Mentor

Machine Learning Engineer (Manager) Belfast - 20 Adelaide Street posted: Posted 30+ Days Ago

Senior Software Engineer, Lab Software Cambridge, MA USA Your Impact at LILA Join us in shaping the future of science! We are seeking Senior Software Engineers with backend experience to join our Lab Software Team (LaS), where you'll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you! About The Team The Lab as Software Team (LaS) acts as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab. What You'll Be Building - Design & Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications. - Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability. - Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability. - Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads. - Cloud & Infrastructure: Leverage AWS services, Kubernetes and modern DevOps

Staff Machine Learning Engineer Boise, ID - Main Site posted: Posted 21 Days Ago

Principal Solutions Architect, AI Ecosystem & Alliances U.S. Remote About the Role We are seeking a technically fluent Principal Solutions Architect to lead our strategic partnership strategy across the enterprise AI infrastructure ecosystem. You will define joint value propositions that articulate the combined strength of our technology alongside partner platforms, creating differentiated solutions across the full AI stack. This role sits at the intersection of partnership strategy, technical architecture, and field enablement. You will be responsible for shaping long-term alliance roadmaps, engaging credibly with solution architects, and preparing global GTM teams to effectively position joint solutions. Key Responsibilities Partnership Strategy & Alliance Management - Ecosystem Leadership: Lead alliance strategy across cloud providers, silicon vendors, MLOps platforms, enterprise Linux/container platforms, and vector database providers. - Joint Business Planning: Build structured business plans with shared objectives, integration milestones, and multi-year roadmaps. - Executive Relationships: Cultivate relationships from C-suite sponsors to technical architects to maintain long-term strategic alignment. - Market Assessment: Continuously identify new integration opportunities and negotiate partnership frameworks in collaboration with Legal and BizDev. Joint Solution Development & Architecture - Full-Stack Architecture: Define architectures spanning data ingestion, feature engineering, model training, fine-tuning, and inference serving. - Technical Integration: Drive certified workstreams across priority areas: - Enterprise Linux & Containers: Certified integrations with platforms like OpenShift to ensure AI workloads are deployable in hardened environments. - Orchestration: Develop validated deployment architectures with Kubernetes optimized for AI workloads. - Vector Databases: Build integrations for semantic search and Retrieval-Augmented Generation (RAG) workflows. - Engineering

Software Development Engineer - Adobe Analytics Bucharest posted: Posted 23 Days Ago

Sr AI Solution Architect, Data & AI Specialist Solutions Architect team Melbourne, Victoria, AUS Amazon Web Services (AWS) is leading the next phase of AI adoption and is seeking a hands-on AI Specialist Solution Architect (SSA). AWS Specialist Solutions Architects (SSAs) are technologists with deep domain-specific expertise, able to address advanced concepts and feature designs. As part of the AWS sales organization, SSAs work with customers who have complex challenges that require expert-level knowledge to solve. SSAs craft scalable, flexible, and resilient technical architectures that address those challenges. This might involve guiding customers as they refactor an application or design an entirely new cloud-based system. Specialist SAs play a critical role in capturing customer feedback, advocating for roadmap enhancements and anticipating customer requirements as they work backwards from their needs. As domain experts, SSAs also participate in field engagement and enablement, producing content such as whitepapers, blogs, and workshops for customers, partners, and the AWS Technical Field. This role focuses on converting AI ambition into programs that can be delivered, operated, and scaled in production environments. Key job responsibilities • The AI Specialist SA team builds technical relationships with customers of all sizes and operate as their trusted advisor, ensuring they get the most out of the cloud at every stage of their journey while adopting GenAI/ML and Agentic technologies across their organisation. • You'll manage the overall technical relationship between AWS and our customers, making recommendations on security, cost, performance, reliability and operational efficiency to accelerate their challenging GenAI/ML

Machine Learning Engineer - ML Applications Porto Alegre, Rio Grande do Sul, Brazil

Applied AI Engineer San Francisco Bay Area | OnSite Role Summary: Own the 0→1. You'll turn vague customer use cases into working proofs-of-concept that showcase what Mem0 can do. This means rapid full-stack prototyping, stitching together AI tools, and aggressively experimenting with memory retrieval approaches until the use case works end-to-end. You'll partner closely with Research and Backend, communicate trade-offs clearly, and hand off winning prototypes that can be hardened for production. What You'll Do: - Build POCs for real use cases: Stand up end-to-end demos (UI + APIs + data) that integrate Mem0 in the customer's flow. - Experiment with memory retrieval: Try different embeddings, indexing, hybrid search, re-ranking, chunking/windowing, prompts, and caching to hit task-level quality and latency targets. - Prototype with Research: Implement paper ideas and new techniques from scratch, compare baselines, and keep what wins. - Create eval harnesses: Define small gold sets and lightweight metrics to judge POC success; instrument demos with basic telemetry. - Integrate AI tooling: Combine LLMs, vector DBs, Mem0 SDKs/APIs, and third-party services into coherent workflows. - Collaborate tightly: Work with Backend on clean contracts and data models; with Research on hypotheses; share learnings and next steps. - Package & handoff: Write concise docs, scripts, and templates so Engineering can productionize quickly. Minimum Qualifications - Full-stack fluency: Next.js/React on the front end and Python backends (FastAPI/Django/Flask) or Node where needed. - Strong Python and TypeScript/JavaScript; comfortable building APIs, wiring data models, and deploying quick demos. - Hands-on with the LLM/RAG stack:

Senior Deep Learning Software Engineer - Autonomous Vehicles 4 Locations posted: Posted 2 Days Ago

Software Engineer II, Lab Software Cambridge, MA USA Your Impact at LILA Join us in shaping the future of science! We are seeking a Software Engineer II with backend experience to join our Lab Software Team (LaS), where you'll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you! About The Team The Lab as Software Team (LaS) acts as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab. What You'll Be Building - Design & Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications. - Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability. - Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability. - Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads. - Cloud & Infrastructure: Leverage AWS services, Kubernetes and modern

Sr Applied Scientist, Generative AI/ML Seattle posted: Posted 24 Days Ago

SecOps Business Development Solution Consultant Vancouver, BC, Canada Fortinet seeks a Business Development Solutions Consultant with experience in Security Operations (SecOps) As a sales engineering specialist you will use your deep technical understanding of Fortinet's advanced security products (SecOps) to convert that knowledge into a high-level conversation with our clients. Business Development Solutions Consultant's will have the capacity to demonstrate how Fortinet's Fabric can be leveraged to increase a customer's protection and defense against cybersecurity attacks by mitigating risks across multiple platform and attack vectors. Business Development Solutions Consultant's will have a clear understanding on how customers can utilize Fortinet's solutions for a broad, integrated, and automated approach to securing users, devices, applications, and edges everywhere, making possible a digital world people can always trust.

Senior AI Machine Learning Scientist 3 Locations posted: Posted Yesterday

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Software Engineering - DevDiv Core AI CZ

Senior Software Engineer, Data Cambridge, MA USA; San Francisco, CA USA Your Impact at LILA Join us in shaping the future of science! We are seeking Senior Software Engineers with backend experience to join our Data Platform Team (Data), where you'll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you! About The Team The Data Platform Team (Data) builds and support the data systems that underpins Lila's AI Science Factory™. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence™, so the science moves faster and each experiment makes the next one smarter. What You'll Be Building - Design & Build APIs: Design and build high-performance, secure, and well-documented APIs that integrate with AI-driven applications. - Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability. - Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads. - Cloud & Infrastructure: Leverage AWS services, Kubernetes and

On-Device ML Integration Engineer, Graphics, Games and Machine Learning Cupertino, United States of America Imagine being at the forefront of an evolution where cutting-edge AI meets the elegance of Apple silicon. The On-Device Machine Learning team transforms groundbreaking research into practical applications, enabling billions of Apple devices to run powerful AI models locally, privately, and efficiently. We stand at the unique intersection of research, software engineering, hardware engineering, and product development, making Apple the leading destination for machine learning innovation. Our team builds the essential infrastructure that enables machine learning at scale on Apple devices. This involves onboarding cutting-edge architectures to embedded systems, developing optimization toolkits for model compression and acceleration, building ML compilers and runtimes for efficient execution, and creating comprehensive benchmarking and debugging toolchains. This infrastructure forms the backbone of Apple's machine learning workflows across Camera, Siri, Health, Vision, and other core experiences, contributing to the overall Apple Intelligence ecosystem. If you are passionate about the technical challenges of running sophisticated ML models across all devices, from resource-constrained devices to powerful clusters, and eager to directly impact how machine learning operates across the Apple ecosystem, this role presents an exciting opportunity to work on the next generation of intelligent experiences on Apple platforms. We are seeking a seasoned ML Engineer with broad experience and an in depth understanding of machine learning, models and infrastructure. In this senior role, you will ensure Apple's inference stack allows integrating ML workflows end-to-end with excellent user experience, flawless functionality, and maximum performance.