Machine Learning Jobs in London

• London
• Hybrid
• £190,000 – £230,000 pa
• Director · manages people

Lead a team of Technical Deployment Leads embedded with strategic enterprise customers across EMEA, owning engagement portfolio health and delivery quality. Player-coach role: hire and manage TDLs, set delivery strategy, run executive relationships and steering committees, and personally lead the most complex engagements from SOW through production deployment. Requires credibility in architecture discussions and depth in enterprise AI/ML delivery.

Claude

• London
• Hybrid
• Lead · manages people
• Permanent

Leads a small, high-agency research team setting the scientific agenda for AI safety, with a focus on large language models and safety-critical systems. Involves conducting and overseeing red-teaming and evaluations in high-risk domains such as CBRN and cybersecurity, publishing at top conferences, and mentoring researchers while aligning work with commercial goals.

Python · OpenAI o1 · Metaview

• London
• Hybrid
• Senior
• Permanent

Lead the development of novel safety evaluations quantifying AI risks in high-impact domains such as CBRN and Cyber, executing original technical research from concept to publication. Shape the R&D agenda, contribute to client delivery and red-teaming for frontier labs, and engage externally with the global research community and government stakeholders.

Anthropic · GDM · Meta +2

• London
• Hybrid
• Lead · manages people
• Permanent

Lead a team of ML engineers and applied scientists building synthetic data from generative world models like GAIA-3, turning them into a production engine for training-grade driving data. Own the pipeline end to end, from checkpoint and large-scale GPU inference to artefacts landing in driving-model training, while setting technical direction on rig transfer, pose transfer and controllability.

Python · PyTorch · GPU +1

• London
• Hybrid
• £120,000 – £150,000 pa
• Director · manages people

Lead and build a data science function at a fintech, owning strategy across risk, affordability and lending decisioning. Hands-on work designing and deploying machine learning models using credit risk, Open Banking and customer data, with a focus on model governance, MLOps and AI-powered decisioning alongside Product, Engineering and Credit Risk teams.

Python · SQL · MLOps +1

• London
• Senior
• Permanent

Processes and QC's paired single-cell RNA-seq and scATAC-seq at scale, building Nextflow pipelines and multimodal training datasets in Zarr for GPU-accelerated model training. Partners with wet lab scientists and ML modellers, contributing to evaluation frameworks that test whether models capture meaningful biology.

STARsolo · Alevin-fry · Chromap +7

• London
• On-site
• Mid-level
• Permanent

Build a greenfield deep learning research stack for a centralised trading book, working in pod-like teams with shared capital and strategic influence. Focus is deep-learning-first: neural networks, transformers, LLM-driven research, multi-modal modelling, NLP and agentic/autonomous research systems, including LLM fine-tuning for regression and forecasting.

GPUs

• London
• On-site
• Mid-level
• Permanent

Join a growing machine learning team at a tech-centric prop trading fund, building and maintaining training and inference infrastructure that moves models from concept to production. The role spans neural networks, random forests, gradient-boosted trees and ensembles, with a focus on tightening research feedback cycles and applying strong mathematical foundations to real trading problems.

PyTorch · Jax · TensorFlow

• London
• Senior

Own the end-to-end technical delivery of AI initiatives, starting with the Clinical Brain, a Class II medical device combining an AI layer with deterministic components. Work with clinical, quality and data teams on NLP, LLMs, knowledge graphs, evaluation pipelines and LLMOps, building to regulated safety and traceability standards.

Neo4j · Cypher · GraphRAG +6

• London
• Hybrid · 3 days in office
• Senior
• Permanent

Builds and operates production ML systems for document classification and extraction, using LLMs/VLMs and traditional ML to process government identity documents at scale. Owns features from RFC through deployment, optimising GPU inference and training/evaluation pipelines in a Python, AWS and Kubernetes stack, while mentoring engineers and leading technical design.

TensorFlow · PyTorch · Triton +5

• London
• Hybrid · 3 days in office
• Senior

Join the Computational Sciences team to design novel large-molecule therapeutics using a cutting-edge AI drug design engine. You will develop computational and machine learning methods to predict biologics properties from sequence, benchmark models, and analyse lab data to guide early discovery through candidate selection.

AlphaFold

• London
• Hybrid · 3 days in office
• Lead

Owns the safety assessment strategy for drug discovery projects from inception to regulatory submission, working with small molecule and biologics platforms. Designs screening cascades, authors and defends regulatory toxicology sections, and manages CRO relationships for outsourced wet-lab work. Also guides development of an AI predictive toxicology platform with ML researchers.

AI/ML

• London
• Senior

Customer-facing pre-sales architect driving adoption of Databricks' AI product line across a local EMEA territory, paired with an Account Executive to design and execute engagement strategies. Leads design and implementation of agentic AI use cases using Agent Framework, AgentBricks and MLflow, and acts as tier-3 escalation for complex field challenges.

Databricks · MLflow · Databricks Agent Framework +7

• London
• Hybrid
• Permanent

Builds ground-truth datasets and computer vision classifiers that describe complex driving scenes, spanning road geometry, spatial relationships, road users and driving behaviour. Works with internal customers to define annotation tasks and acceptance criteria, curates datasets, and integrates classifiers with enrichment infrastructure for corpus analysis and scenario mining.

PyTorch · SQL

• London
• Lead · manages people
• Permanent

Lead the science vision for Trusted Supply, safeguarding advertiser trust across Amazon Advertising by developing algorithms for brand safety, suitability scoring, fraud detection, viewability prediction and privacy-preserving measurement. The role spans multi-year research direction, publication roadmaps, cross-team modelling frameworks and production systems serving billions of ad impressions daily, alongside hiring and mentoring applied scientists and research engineers.