Top Machine Learning Jobs in London

Leads application engineering for an AI-powered email product across backend, mobile, and desktop platforms. Designs reliable AI workflows involving orchestration, state, tool use, retries, fallbacks, and failure handling. Builds APIs connecting AI capabilities to product experiences, makes architectural trade-offs, establishes observability and operational excellence, and leads a small senior engineering team through mentorship, design reviews, and code reviews. Partners with ML leadership to deliver scalable, reliable, and maintainable production systems.

Lead application engineering for an AI-powered email product across backend, mobile, and desktop platforms. Design reliable AI workflows involving orchestration, state, tool use, retries, fallbacks, and failure handling. Build APIs connecting AI systems to product experiences, make architecture and scalability decisions, mentor senior engineers, and establish strong observability, monitoring, testing, security, and operational practices. Partner with ML leadership to ship fast, reliable, maintainable product experiences.

Own end-to-end machine learning systems for Depop’s Trust Detection team, addressing phishing, counterfeit goods, fraud, abuse, and prohibited content. Responsibilities include problem framing, data strategy, deep learning and LLM development, multimodal modeling, deployment, experimentation, evaluation, and production iteration. The role partners with Trust, Policy, and Product teams to build scalable, robust systems in ambiguous and adversarial environments and communicate technical trade-offs and impact.

Join as a graduate quantitative researcher to design, build, test and deploy statistical and machine learning models for pricing, forecasting and signal discovery using large-scale market and unstructured data. Collaborate with researchers, traders and engineers to monitor production models, refine assumptions, and accelerate research-to-production using AI-enabled workflows.

Research and develop human-centric generative video models for facial expression control, head motion, lip synchronization, and realistic talking-head animation. Responsibilities include fine-tuning video diffusion models, creating large-scale audio/video datasets and training pipelines, exploring expression editing and multi-view consistency, and collaborating with product and creative teams. The role also involves staying current with video generation, speech-driven animation, and 3D-aware neural rendering research.

Lead technical discovery, solution design, demonstrations, and proof-of-concept support for Anaconda’s AI and data science platform across EMEA. Partner with account executives on complex deals, create reusable technical content, represent customer needs to product and engineering, and coordinate with cross-functional teams through implementation handoff. Manage multiple opportunities independently while improving technical win rates, deal expansion, sales velocity, and regional pipeline development.

Lead Boltz's enterprise sales, converting inbound interest into $1M+ ACV platform contracts. Drive high-value deals, scope complex engagements, negotiate contracts, expand accounts, and build a repeatable enterprise sales motion while partnering with CEO, science, and product teams.

Develop and validate agentic AI capabilities for patent analysis using machine learning, NLP, LLMs, RAG, hybrid search, and agentic workflows. Analyze large-scale intellectual property datasets, design experiments, evaluate and benchmark models, define reasoning strategies, and translate findings into product recommendations. Collaborate with product managers, IP experts, and engineers to deliver scalable, customer-facing solutions.

Develop and validate agentic AI capabilities for patent analysis using machine learning, NLP, LLMs, generative AI, retrieval, and hybrid search. Define multi-step reasoning workflows, analyze large-scale intellectual property datasets, establish model evaluation and benchmarking practices, and translate experiments into product recommendations. Collaborate with product teams, intellectual property experts, and engineers to deliver scalable, customer-facing solutions.

Leads complex machine learning delivery and Defence-sector strategy, translating client challenges into technical roadmaps, scoping projects, managing client relationships, and supporting technical sales. Writes production-grade Python, serves as a machine learning authority, develops Generative AI and agentic AI solutions using LLMs, and mentors and manages data scientists.

Develop and scale NVIDIA Inception’s European startup ecosystem by identifying, technically assessing, recruiting, enabling, and nurturing AI and accelerated-computing startups. The role advises founders and technical leaders on CUDA, NVIDIA SDKs, AI frameworks, GPU infrastructure, and platform adoption; leads technical workshops; translates ecosystem feedback into product insights; collaborates with venture capital firms and internal teams; and supports sales and enterprise customer motions. Travel across Europe is required approximately 40% of the time.

Design and scale AI-driven solutions for fashion imagery and video, using computer vision, deep learning, generative AI, LLMs, and multimodal processing. Build reliable data pipelines, fine-tune and deploy models, standardize AI workflows, implement MLOps practices, develop evaluation frameworks, and partner with cloud infrastructure and product teams. Promote responsible AI by identifying and mitigating bias and risk while delivering production-ready, personalized shopping experiences.

Lead and scale engineering teams building multi-tenant Voice AI, Agent QA, analytics, auto-learning, and workforce management platforms. Own architecture for high-throughput voice data systems, real-time pipelines, telephony integrations, optimization algorithms, and enterprise compliance. Recruit and develop senior engineers and managers, establish engineering standards, guide cross-functional roadmap alignment, and deliver reliable production systems across global geographies.

Build and operate ML platform capabilities that move models from experimentation into reliable production. Responsibilities include automating training, validation, deployment, retraining and rollback; operating batch and online inference services; implementing CI/CD, observability, monitoring, alerting and incident response; improving scalability, security and cost efficiency; and developing production-grade Python tooling. The role collaborates with research, software, platform, security, data and product teams.

Design, build, and operate reliable, scalable AI/ML platform infrastructure. Develop observability, resilience, security, and automation tooling, own NFRs, participate in on-call rotations, troubleshoot production issues, and collaborate cross-functionally to support large-scale AI deployments.

Own strategic client relationships and deploy Valence's generative-AI coaching across Fortune 500 accounts. Drive adoption, renewals, expansion, and measurable behavior change while partnering with Sales, Ops, and Product to shape roadmap and ensure successful implementations.

Lead design, development, and verification of autonomy solutions for defense: write perception and planning algorithms, prototype and deploy ML models, optimize performance, build system architectures, collaborate cross-functionally, mentor junior engineers, and test/debug with attention to documentation and emerging AI techniques.

Lead the Therabody mobile app roadmap and deliver cross-functional features that integrate software, firmware, hardware, and AI. Drive end-to-end execution from strategy and user research to engineering delivery, A/B testing, analytics, and go-to-market launch while partnering with design, marketing, and product development to improve engagement and conversion.

Design, build, and maintain large-scale, high-performance distributed systems and backtesting platforms. Write production-quality Python on Linux, learn/use C++, and apply strong data-structures, algorithms, concurrency, and system-programming skills. Collaborate with researchers to support scalable quantitative research and production trading workflows.

Own Quadrants, an open-source Python compiler for performance-critical numerical computing. Responsibilities include API design, intermediate representation and lowering, multi-backend support, compiler optimization, GPU kernel development, numerical primitives, benchmarking, regression tracking, and roadmap ownership. The role combines GPU programming, compiler engineering, Python API design, performance optimization, user engagement, and open-source product direction, with potential to lead a small team.

Design and deploy machine learning models for financial document processing, optimize large language models, collaborate with cross-functional teams, and guide junior peers in a fast-paced environment.

Lead design and delivery of cloud-based data engineering, analytics and AI solutions. Advise clients, capture requirements, create solution architectures, build data platforms and ETL/ELT pipelines, develop Power BI dashboards, integrate ML/Generative AI, and lead/mentor project teams to deliver scalable, secure data products.

Deliver and validate statistical logic for a company-wide experimentation platform. Prototype analyses in Python, perform independent QA of platform outputs, investigate discrepancies, automate QA where possible, collaborate with Data Engineering, BI, ML and product teams, and contribute to future statistical and ML initiatives.

10-week internship developing client-facing solutions, financial research, and technical systems. Tasks include debugging Python, deploying infrastructure, building REST APIs and data pipelines, shipping production-quality code, supporting clients, testing bespoke workflows, and liaising between clients, product, and engineering to drive product enhancements.

As a Principal Consultant, lead engagements in Capital Markets, driving innovation, digital transformation, and improving user experience across multiple financial sectors while collaborating with cross-functional teams.