247 jobs for “ML Architect”
Isomorphic Labs London
Lead translational pharmacology for an AI-first drug discovery team, shaping neurodegeneration strategy and target validation. Bridge dry-lab AI models with experimental biology, designing screening cascades and managing CRO studies to advance programs from target ID to portfolio entry.
Isomorphic Labs London
Lead formulation strategy for small molecules across drug discovery and preclinical development, designing technologies such as solid dispersions and co-crystals to improve solubility, stability and manufacturability. Interpret stability studies using ICH and ASAP methods, author regulatory submissions, and work with external CROs alongside AI/ML drug design teams.
Faculty London
Lead the design, build and deployment of production-grade ML systems for national security and AI safety clients, including capability testing of frontier models. Act as a technical advisor to customers, define best practices for deploying ML at scale, and mentor junior engineers. Distinct for its focus on red teaming, evaluation and high-stakes government and frontier lab work.
Wayve London
Lead large-scale training and post-training for Gaia, Wayve's world model that predicts future driving video and runs closed-loop with the driving stack. Own model architecture decisions, push autoregressive rollouts toward longer, more stable generation, and make the model deployment-ready. Partner with research, applications, simulation engineering and cloud teams, mentoring and setting technical direction.
Wayve London
Develops, tunes and validates trajectory-generation and motion-control algorithms that turn the AI Driver's outputs into safe, smooth vehicle motion across multiple platforms. Owns production-quality, latency-sensitive C++ control software through the full lifecycle, using simulation, closed-loop evaluation and on-road testing to characterise controller behaviour and track comfort, tracking-error and safety KPIs.
Faculty London
Set technical direction for complex AI/ML projects, leading delivery of large-scale platforms in high-risk national security environments. Define roadmaps across multiple workstreams, justify architectural decisions to senior stakeholders, and coach engineers while building shared deployment and CI/CD infrastructure. Requires DV eligibility and occasional on-site client work.
Amazon London
Manage a London-based team of associates producing labelled speech and language data for Alexa and Amazon Echo ML systems. Day to day you assign work, monitor queue adherence, volume and quality, hire and train associates, build weekly schedules across competing workflows, and track quality and utilisation metrics. You liaise with program management and global operations leads on risk mitigation and drive process improvement using Kaizen, Six Sigma or lean methods.
Harnham - Data and Analytics Recruitment London £75,000 – £85,000 pa
Owns the infrastructure, deployment and operational excellence of production machine learning systems within a growing AI and data organisation serving the public sector. Builds ML orchestration pipelines with Dagster, Airflow or Prefect, runs Kubernetes and Terraform/Bicep infrastructure, and maintains CI/CD and observability for models and LLM-powered solutions, working closely with data scientists and client-facing teams.
eFinancialCareers London
Joins a proprietary trading firm's research team to build machine learning and statistical models for quantitative and trading applications, working with large, noisy, high-dimensional datasets. Involves time-series, Bayesian, deep learning and reinforcement learning approaches, rigorous experiment design, and collaboration with quant researchers, traders and engineers to move models toward production.
University of Hertfordshire Hatfield £39,560 – £46,970 pa
Postdoctoral role delivering research on innovative AI/ML algorithms for predictive modelling and optimisation of agricultural applications from heterogeneous data, as part of an Innovate UK-funded collaborative project. Involves developing AI/ML software tools, data management and analysis, supporting the Principal Investigator on project milestones, and contributing to publications and reports.
Vallum Associates London £475 – £500 pd
Data scientist role focused on collecting and analysing large datasets, building experimental models and machine learning applications in Python, and performing complex statistical analysis. Involves leading small teams on data science products, developing classical ML and LLM solutions with prompt and RAG techniques, and mentoring junior data scientists. Hybrid working with two days per week in the London office.
Medtronic London £76,800 – £115,200 pa
Designs, builds and maintains AWS and on-prem infrastructure used by ML engineers, data scientists and product teams, with a strong focus on Kubernetes, Helm, Terraform/OpenTofu and GitOps delivery. Also handles platform service requests, incident diagnosis and reliability improvements, working across engineering teams in a surgical AI centre of excellence.
Anthropic London
A four-month, full-time research fellowship working on empirical AI projects in either ML systems/performance or reinforcement learning, using external infrastructure like open-source models and public APIs. Fellows receive direct mentorship from Anthropic researchers and aim to produce a public output such as a paper submission, with projects spanning CPU simulators, accelerator backends, synthetic data pipelines, and RL environments.
Helical London
Provide scientific leadership across model evaluation and applied use cases, ensuring foundation models stay grounded in drug development and translational research challenges. Act as a key scientific partner to the research team, mentor junior colleagues, and work with Product and Business Development to turn biology and ML into customer-facing deliverables.
Helical London
Lead scientific evaluation and applied use of foundation models in drug discovery and translational research. Act as a senior individual contributor and scientific partner, mentoring junior colleagues while working with Product and Business Development to turn biology and ML into customer-facing deliverables as the team scales.
