227 jobs for “Machine Learning Engineer cambridge”
PhysicsX New York, United States US$150,000 – US$250,000 pa
Builds and deploys customer-facing applications on top of physics AI models, working directly with clients, data scientists and ML engineers. Involves full-stack work: FastAPI REST APIs and Python microservices, plus cloud deployment with Helm, Kubernetes, Terraform and AWS/Azure. Expect on-site travel to customer sites for 3-4 weeks per quarter.
PhysicsX Singapore
Customer-facing engineering role building and deploying applications that put physics AI models into production for industrial clients. You will work directly with customers, data scientists and ML engineers, prototyping tools, iterating on user feedback, and building Python FastAPI microservices deployed on Kubernetes, Terraform and AWS/Azure.
Anthropic London £165,000 – £190,000 pa
Pre-sales architect acting as a trusted technical advisor to large enterprises, helping them integrate and deploy Claude across their technology stack. Combines deep LLM expertise with customer-facing work, from technical discovery and evals to scalable architecture design, while feeding integration insights back to Product and Engineering.
Thought Machine Lisbon, Portugal
Full-stack role building end-to-end features across web applications and backend services, with React and TypeScript on the front end and REST APIs behind. Engineers own requirements from design and task breakdown through testing, debugging and production, working in a cross-functional team for banking clients.
Thought Machine Lisbon, Portugal
Owns complex, ambiguous technical challenges end-to-end, shaping long-term platform architecture and company-wide engineering standards. Drives adoption of AI tooling, leads technical interviews, and mentors senior engineers while acting as a link between leadership and engineering teams. Based in the Lisbon office, requiring three days a week onsite.
Palo Alto Networks London
Acts as "customer zero" and advocate for Identity Security, defining and validating enterprise architectures for machine identity, secrets governance and agentic identity management. Produces technical content such as blogs, whitepapers and deep-dive decks, builds reference architectures and demos, and partners with specialist sellers and solutions teams on complex customer engagements. Also feeds product insights and leads market education through executive briefings and conference talks.
Databricks London
Lead and scale the UK Forward Deployed AI Engineering team, delivering professional services engagements that help EMEA customers productionise GenAI and ML applications. The role combines people leadership, executive customer relationships, and cross-functional work with Product, Research and Sales to shape delivery models and the product roadmap.
Aioi Nissay Dowa Europe Oxford £81,322 – £112,488 pa
This role involves leading research in privacy-preserving generative AI, focusing on techniques like differential privacy, federated learning, and secure inference. The scientist will design and validate machine learning models, translate research into deployable systems, and contribute to publications and collaborations within a multi-partner environment. Emphasis is placed on responsible AI, reproducibility, and mentoring junior team members.
eFinancialCareers London
Lead the build-out of a hedge fund's machine learning function, defining research strategy and hiring a team of ML researchers and engineers. Directs work in deep learning, reinforcement learning, probabilistic and time-series modelling, and generative AI, partnering with quant and investment teams on alpha generation, forecasting, portfolio construction, risk and execution. Combines hands-on technical direction with strategic leadership.
Isomorphic Labs London
Builds greenfield machine learning models and algorithms for drug discovery, designing new architectures, running experiments, and scaling training and inference frameworks. Works in an interdisciplinary team of ML scientists and domain experts, with opportunities to lead projects and mentor others depending on experience.
University of Oxford Oxford £39,424 – £43,984 pa
Develops 3D reconstruction and multi-view data fusion methods for neonatal cranial ultrasound, validating them on data from the neonatal intensive care unit. Works at the intersection of 3D computer vision, neural rendering and medical image analysis, including physics-informed rendering models for view-dependent acoustic appearance. Based in a multidisciplinary lab alongside deep learning researchers, software engineers and neonatologists.
Isomorphic Labs London
Translates Isomorphic Labs' security strategy into engineering delivery, steering a multi-quarter InfoSec roadmap spanning Cloud Security, Platform IAM and Secure SDLC. Partners directly with engineering and ML teams to unblock architectural issues, secure drug discovery pipelines and build data-driven dashboards giving the CISO visibility into program health and risk metrics. Reports to the CISO with a functional tie to the TPM Discipline Lead.
The Alan Turing Institute London £96,000 – £115,000 pa
Provides scientific and strategic leadership for the AI for Physical Systems research area, shaping a portfolio spanning probabilistic modelling, uncertainty quantification, efficient architectures and physics-informed machine learning. Leads a multidisciplinary team of researchers and engineers, taking methods from foundational research through to deployment on real-world resilience challenges, and builds collaborations across academia, government and industry.
Amazon London
Lead teams of technicians running AWS data centre operations, owning the full infrastructure lifecycle from rack installation and break-fix maintenance to decommissioning. The role spans building new sites, vendor management, health and safety compliance, and adopting high-density GPU, AI accelerator and liquid-cooling technologies, with a focus on automation and operational metrics.
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. High visibility with senior leadership in a strategic deep learning and HPC area.
