Machine Learning Jobs

• Singapore
• Hybrid
• Lead

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.

NumPy · SciPy · Pandas +4

• Singapore
• Hybrid
• Senior

Build physical foundation models for industrial engineering, scaling training across multi-GPU cloud compute and turning research prototypes into robust, optimised implementations. Work at the intersection of data science and software engineering, owning research work-streams and translating results into reusable libraries, tooling and products alongside scientists, customers and partners.

PyTorch · JAX · NumPy +7

• United Kingdom
• Hybrid
• Senior

Develop algorithms and optimizations for NVIDIA's LPX inference and compiler stack, working at the intersection of large-scale systems, compilers, and deep learning. The role involves building high-performance runtime and compiler components, mapping inference workloads onto future hardware, and collaborating with hardware architects on codesign. Distinct focus on LLVM/MLIR, graph transformations, and spatial accelerators.

LLVM · MLIR · TensorFlow +3

• London
• Hybrid
• Director
• Permanent

Owns the architecture, strategy and integrity of safety cases for robotaxi and OEM ADAS products, defining top-level claims, argumentation structures and evidence traceability. Sits independently from Engineering and Product, providing expert challenge and oversight across AI/ML, systems, validation and operational safety. Focuses on safety arguments for AI-enabled autonomous driving, including functional safety, SOTIF and post-deployment monitoring.

ISO 26262 · ISO 21448 · ISO/PAS 8800 +2

• Reading
• Senior

Engage a small set of strategic software companies to integrate NVIDIA's AI and computing platforms into their products, acting as a trusted technical advisor on agentic AI, open models and GPU-accelerated computing. Provide sample code, SDKs and demo pipelines to accelerate onboarding, while mapping the developer ecosystem and feeding field insights back to product teams. Also represents NVIDIA at industry and developer events.

NVIDIA · NIMs · SDKs

• Cambridge, United States
• Hybrid · 3 days in office
• Lead

Lead the safety assessment strategy for small molecule and biologic drug discovery projects from inception to regulatory submission, designing screening cascades and mechanistic experiments. Partner with machine learning researchers to build predictive toxicology models and manage external CROs for all wet-lab data generation, while mentoring junior scientists.

KNIME · Python

• London
• Hybrid · 3 days in office
• Lead

Drive DMPK strategy across drug discovery projects, designing screening cascades and mechanistic experiments with an AI-first approach. Integrate DMPK, PD and toxicology data to predict human dose and safety windows, and author regulatory documents. Work closely with Chemistry, Pharmacology and AI/ML platform teams on multiple modalities including biologics and peptides.

R · Python · KNIME

• London
• Hybrid
• Senior
• Permanent

Owns embedded software that connects an autonomous driving AI to vehicle platforms, building integration and adaptation layers across hardware. Works on inference integration, vehicle data, navigation, localisation and motion control interfaces, taking features from design through HIL and vehicle testing. Requires strong modern C++ and Linux/QNX experience on Nvidia and Qualcomm platforms.

Nvidia · Qualcomm · Linux +3

• London
• Hybrid
• Mid-level
• Permanent

Builds and deploys production-grade machine learning systems for national security and AI safety clients, including LLM applications, multi-agent tooling and evaluation of frontier models. Involves leading technical scoping and architecture decisions, defining deployment standards, and advising customers, working alongside engineers, data scientists and commercial leads.

AWS · Azure · GCP +5

• London
• Hybrid
• Mid-level
• Permanent

Builds and deploys production-grade machine learning systems for national security and AI safety clients, including LLM applications, multi-agent tooling and evaluation of frontier models. Involves leading technical scoping and architecture decisions, defining deployment standards, and advising customers while working alongside engineers, data scientists and commercial leads.

AWS · Azure · GCP +5

• London
• Director · manages people
• Permanent

Lead the platform engineering team owning hybrid on-prem and cloud compute, Kubernetes clusters, and MLOps infrastructure such as Kubeflow notebooks, GPU training and model serving. Set architectural direction, mature CI/CD, observability and security controls, and ensure scientific compute meets the needs of ML and data science teams. Reports to the VP of Engineering in a matrixed TechBio environment.

Kubernetes · Kubeflow · ISO 27001 +2

• London
• Mid-level
• Permanent

Backend engineering role focused on the systems that keep ChatGPT reliable at scale, spanning shared services, APIs, asynchronous processing and infrastructure migrations. Engineers write production code, own rollout and rollback, and improve monitoring and diagnostics, with on-call and incident response duties. Distinct for its close coupling of infrastructure work to a high-traffic consumer product.

ChatGPT · APIs · Cloud Infrastructure +2

• London
• Hybrid
• Permanent

Deploys and adapts proprietary generative biology models into pharmaceutical and biotech customer environments, building production-grade API integrations, model-serving infrastructure and ML data pipelines. Combines deep generative-modelling research with customer-facing delivery, fine-tuning models and feeding insights back to research and product teams. Hybrid role with on-site work at international partner locations.

AlphaFold · NeurIPS · ICML +2

• London
• Hybrid
• Mid-level
• Permanent

Serve as the technical bridge between frontier generative biology models and pharmaceutical/biotech customers, owning end-to-end deployment, API integration and model-serving infrastructure. Work embedded on-site with partners, translating scientific requirements into production-grade systems while feeding customer insights back to product and research teams.

AWS · GCP · Azure +2

• Gloucestershire
• Hybrid
• £51,000 – £60,500 pa
• Senior

A varied engineering role spanning research, product and service development, with a focus on AI and computer vision (object detection and tracking). You lead software design, development, testing and deployment within multidisciplinary teams, and act as a subject matter expert advising clients on architecture. Python and C++ on Linux, with DevOps, MLOps and SDLC practices.

Red Hat · Ubuntu · Pandas +6