228 jobs for “Deep Learning Engineer”
PhysicsX Singapore
Join a new Singapore research team building physical foundation models for industrial engineering, translating physics and simulation challenges into mathematical formulations. You will develop deep learning and probabilistic models for physical systems, run large-scale experiments, and own research workstreams while publishing and presenting to customers and the community.
PhysicsX New York, United States US$120,000 – US$240,000 pa
Builds and deploys deep learning and probabilistic models to predict and control physical systems, working alongside simulation engineers and customers. Owns data pipelines and production-ready models, and travels to customer sites roughly 3-4 weeks per quarter to co-develop solutions on-site.
Faculty London
Lead the design, build and deployment of production-grade machine learning systems for clients across life sciences, government and finance. Work spans architectural scoping, scalable cloud and Kubernetes infrastructure, and acting as a trusted technical advisor to customers while mentoring junior engineers.
Faculty Remote (UK)
Lead the design, build and deployment of production-grade machine learning systems for defence-sector clients, covering architecture, scalable infrastructure and MLOps standards. Work cross-functionally with engineers, data scientists and commercial teams while acting as a trusted technical advisor to customers. Requires eligibility for UK Security Clearance and 2-4 days per week on client sites.
NVIDIA United Kingdom
Lead NVIDIA's developer strategy with a major cloud service provider, driving GPU acceleration adoption across AI and generative AI workloads. The role blends developer advocacy, product management and business development, building engineering partnerships and hosting summits and meetups. It offers high visibility with senior leadership given the strategic priority of deep learning platforms.
NVIDIA Cambridge
Lead security research, architecture and implementation for next-generation networking products, taking a hands-on role in hardware and software security primitives. Work across internal teams and external partners on open-source software, IO interfaces (I2C, I3C, SPI, UART, USB, PCIe), RISC-V, root-of-trust and secure boot architecture.
Amazon London
Hands-on data science role focused on Alexa for Shopping, building and measuring multimodal conversational systems powered by large language models, information retrieval, recommender systems and knowledge graphs. Day to day involves analysing huge multimodal datasets, designing and analysing A/B tests, building predictive models and metrics dashboards, and working with applied scientists and engineers to move insights into production.
Cohere London
Research internship focused on building and training large language models, with projects spanning base model training, retrieval augmented generation, evaluation, safety, and finetuning. Interns design and implement novel research ideas, ship state-of-the-art models to production, and publish results through papers, datasets, and code.
Spencer Rose Bristol £450 – £480 pd
Designs, builds and deploys end-to-end AI/ML solutions for a banking client's Coach AI programme, including LLM-powered assistants, copilots and multi-agent agentic systems. Works across NLP, computer vision and voice AI, building ML pipelines and production deployment with MLOps, guardrails and Responsible AI governance. Also acts as senior lead, grooming the internal team and collaborating with stakeholders.
Anthropic London
A four-month, full-time research fellowship focused on empirical AI safety and security projects, using external infrastructure such as open-source models and public APIs, with the goal of producing a public output like a paper submission. Fellows receive direct mentorship from Anthropic researchers, access to shared workspaces in Berkeley or London, and funding for compute and research expenses.
Luminance Cambridge
Join a small R&D team prototyping and implementing new AI approaches, evaluating output quality, efficiency and feasibility against alternative techniques in a data-driven way. Work spans large dataset handling, modelling and evaluation using Python ML frameworks such as PyTorch, TensorFlow and Scikit-Learn, with senior candidates contributing NLP, computer vision or deep learning expertise.
Synoptix Bristol £65,000 – £85,000 pa
Lead the technical vision and delivery of bespoke AI research programmes, spanning object detection, neural network resilience, AI assurance and synthetic data. Day-to-day work includes high-throughput vision systems on NVIDIA Jetson hardware, CUDA/TensorRT acceleration, multi-modal thermal and optical sensing, and real-time tracking, while guiding junior engineers and engaging senior stakeholders.
Harnham - Data and Analytics Recruitment Abingdon US$200,000 – US$220,000 pa
Engineering-focused role taking machine learning solutions from concept to production, covering model design, training, deployment, MLOps, infrastructure and scalability. Works closely with engineering, product and domain experts in a small, highly technical team, with an emphasis on shipping robust production ML systems rather than pure research.
Anthropic London £260,000 – £630,000 pa
Blends reinforcement learning research with engineering, building scalable RL infrastructure, distributed training across GPU clusters, and novel training environments for agentic LLMs. Involves profiling, optimization, caching, and debugging distributed systems, with close collaboration between research and production teams.
OpenAI London
Designs, builds and maintains production harm-detection systems using SQL, Python, machine learning and language models, developing signals, classifiers and pipelines on shared engineering platforms. Owns protection strategy and cross-functional delivery for a harm area or product launch, connecting detection with policy, review, enforcement and measurement. Includes on-call rotation and exposure to sensitive content.
