Machine Learning Jobs

• New York, United States
• Hybrid · 2–3 days in office
• 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.

NumPy · SciPy · Pandas +2

• Singapore
• Hybrid
• Lead

Develops multiphase CFD and DEM models for industrial bioprocess and chemical engineering applications, covering gas-liquid, solid-liquid, VOF and Euler-Euler/Euler-Lagrange approaches, non-Newtonian rheology and coupled reactive physics. Owns meshing strategy, parametric CAD-coupled simulation pipelines, HPC-scale transient runs and surrogate/ML-CFD workflows, working directly with customers to scope and validate models against experimental data.

Star-CCM+ · OpenFOAM · Fluent +5

• London
• Hybrid
• £165,000 – £190,000 pa
• Senior

Partner with founders and startup engineers as a technical advisor, guiding them from evaluation through deployment of LLM applications on the Claude Developer Platform. You'll run technical evaluations, design architectures, develop evaluation frameworks, and feed emerging use cases back to Product and Engineering, with travel to customer sites and events.

Claude · Claude Developer Platform

• London
• Hybrid · 1 day in office
• £255,000 – £325,000 pa
• Lead · manages people

Lead a London-based team building connectivity infrastructure for Claude, including the MCP proxy, OAuth and token management, and official SDKs. The role spans hiring, coaching, roadmap setting with San Francisco partners, and operational rigor for production distributed systems.

MCP · Python · TypeScript +3

• Singapore
• Lead · manages people

Lead technical delivery of physics AI solutions, architecting deep learning models and optimisation methods to predict and control physical systems. Build scalable production data pipelines, mentor junior team members, and collaborate on-site with customers across multiple regions to embed AI models into engineering tools.

NumPy · SciPy · Pandas +2

• Singapore
• Lead

Lead the deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimisation) into customer production environments. Own scoping, architecture and success metrics for data/ML systems, mentor engineers, and work on-site with customers across North America, Europe, Asia and Oceania for 3-4 weeks per quarter.

Python · PyTorch · Pandas +3

• Singapore
• Senior

Build and deploy customer-facing applications that put physics AI models into production, working directly with customers, data scientists and ML engineers. The role spans rapid prototyping, backend development of Python/FastAPI REST APIs and microservices, and cloud deployment using Kubernetes, Helm, Terraform and AWS/Azure. It suits someone who can grasp complex engineering problems across industries and own solutions end-to-end.

FastAPI · Helm · Kubernetes +3

• London
• Hybrid · 1 day in office
• £325,000 – £395,000 pa
• Senior

Builds foundational infrastructure for AI safety, oversight and intervention, including data storage, metrics and evaluation systems, and tooling for human and agentic review. The role also involves running these systems day to day and building multi-layered, real-time defenses against misuse at scale.

Claude Code

• London
• Hybrid · 1 day in office
• £260,000 – £630,000 pa
• Mid-level

Blends research and engineering to advance reinforcement learning for large language models, building agentic capabilities like computer use and autonomous code generation. Involves architecting distributed RL training infrastructure across GPU clusters, designing novel training environments and evaluations, and profiling and optimizing the stack. Works closely with alignment, red team, and production training groups, with a strong pair-programming culture.

PyTorch · TensorFlow · JAX +3

• London
• Hybrid
• £370,000 – £630,000 pa
• Mid-level

Builds and improves the RL training infrastructure researchers rely on, profiling, debugging and rearchitecting bottlenecks across the stack. Partners with researchers and adjacent engineering teams to ship tooling that speeds up training runs, owning reliability and performance end-to-end.

JAX · PyTorch

• London
• Hybrid · 1 day in office
• £260,000 – £630,000 pa
• Mid-level

Join the Pretraining team to develop next-generation large language models, working across model architecture, algorithms, data processing and optimizer development. You'll lead small research projects, design and analyse experiments, and scale distributed training infrastructure to thousands of GPUs, blending research and engineering in a highly collaborative environment.

PyTorch · Kubernetes · GPUs +1

• London
• On-site
• £260,000 – £630,000 pa
• Mid-level

Own critical parts of a production pretraining pipeline, covering performance optimization, observability, reliability and hardware debugging across the full stack. The role splits roughly 50/50 between research and engineering, with on-call incident response during model launches and close collaboration with teams in SF and London.

JAX · TPU · PyTorch +3

• London
• Hybrid
• £375,000 – £640,000 pa

Designs and runs large-scale reinforcement learning experiments to understand how RL behaves as model size, compute and task horizon grow, and builds benchmarks that make long-horizon progress measurable. Sits at the boundary between research and engineering, debugging failures that only appear at frontier scale and shipping validated findings into production training recipes alongside adjacent RL teams.

• London
• Hybrid · 1 day in office
• £325,000 – £390,000 pa
• Senior

Lead and scope multi-month infrastructure projects, making architectural decisions for large-scale distributed systems that train and serve AI models. Work spans Kubernetes clusters, data pipelines, databases, observability and developer tooling, partnering with research and product teams while owning reliability, scalability and security.

Kubernetes · AWS · GCP +6

• London
• Hybrid · 1 day in office
• £225,000 – £255,000 pa
• Senior

You'll act as a trusted technical advisor to high-growth startups building on the Claude Developer Platform, pairing with customer engineering teams on architecture reviews, code contributions and agent design. The role blends hands-on LLM engineering—evaluation frameworks, prompting, deployment—with developer-facing content, workshops and hackathons, feeding insights back to Product and Engineering.

Claude · Claude Developer Platform