Top Machine Learning Jobs in London

Develop, integrate, tune, and validate vehicle trajectory and motion controllers for autonomous and assisted driving systems. Build latency-sensitive, production-quality C++ controls software connecting AI outputs to vehicle actuation and feedback. Use simulation, closed-loop evaluation, and on-road testing to diagnose behavior and validate improvements across vehicle platforms. Collaborate cross-functionally on controller interfaces, system integration, and new vehicle features.

Lead the design, development, and deployment of scalable, production-grade machine learning systems for diverse clients. Define ML deployment standards, make architectural decisions, collaborate with technical and commercial teams, advise customers, and mentor junior engineers. The role requires strong Python and software engineering expertise, experience operationalizing TensorFlow or PyTorch models, cloud architecture, security, infrastructure, Docker, and Kubernetes.

Own Gridsight’s enterprise sales expansion across GB and Ireland, managing the full sales cycle from account prioritization and consultative discovery through tenders, procurement, and contract closure. Build pipeline and forecasting processes from scratch, develop utility partner and channel relationships, and collaborate with technical, delivery, and regional leadership teams. The role targets regulated electricity distribution and system operators with complex, multi-year B2B software sales.

Build and productionize ML and LLM-powered recommendation features serving millions of users. Own end-to-end systems spanning data pipelines, feature engineering, model training, real-time serving, APIs, monitoring, A/B testing, and distributed infrastructure. Collaborate with Product, Design, Engineering, and Platform teams while optimizing performance, cost, latency, reliability, and user experience.

Build, train, optimize, and integrate machine learning and large language model systems for real-time games and interactive experiences. Own projects across the ML pipeline from data preparation and experimentation through production deployment. Collaborate with engineers, artists, writers, and designers to create compelling AI-powered products, with emphasis on performance, latency, efficiency, and creative applications.

Lead the development of AI-enabled products within a consulting environment focused on financial services and energy, utilizing modern AI tools and methodologies.

Design and develop cloud-based data platform solutions, including data pipelines, ingestion, transformation, cleansing, integrations, and data applications. Translate technical requirements into detailed designs, write reliable code, develop test automation, troubleshoot operational issues, tune batch and real-time processing, secure cloud data platforms, and implement CI/CD and monitoring. The role also involves advising client developers and defining efficient operational processes.

Lead the technical direction and delivery of complex machine learning platforms in high-risk environments. Design scalable production ML systems, deployment infrastructure, APIs, testing frameworks, model versioning, and CI/CD pipelines. Define architecture and technical roadmaps, oversee multiple workstreams, guide technology adoption, and manage and coach engineers. The role requires expertise in cloud-native ecosystems, Kubernetes, TensorFlow or PyTorch, agentic systems, and production model operations.

Lead design and delivery of production-grade AI/ML solutions for Market Operations. Manage a team of data scientists and partner with engineering and business stakeholders to build, deploy, monitor, and govern models, establish best practices, and drive measurable operational impact.

Turn utility network data, including AMI, topology, and asset telemetry, into reliable analysis and visualizations. Own customer delivery across pre-sales, pilots, and deployments; lead working sessions; present findings; translate technical concepts; adapt the platform to UK and European grid operators; and build the regional delivery playbook. The role requires strong hands-on data skills, commercial judgment, customer communication, rapid learning, AI-enabled workflows, and comfort operating as an early hire.

Gridsight invites exceptional candidates in the United Kingdom to submit an expression of interest for future opportunities. The company develops SaaS solutions using data, machine learning, and AI to modernize electricity-grid operations, support renewable connections, and orchestrate distributed energy resources. Applicants should explain their achievements, impact, motivation, learning ability, and alignment with Gridsight’s low-ego, high-impact culture.

Lead pricing ML for Rosso: define technical direction, build production-grade price-optimisation and probabilistic imbalance models, bridge modelling and MLOps, and communicate model decisions across teams.

Leads complex, large-scale AI infrastructure and inference engagements with governments, sovereign enterprises, and conglomerates. Responsibilities include executive relationship management, business-case development, account planning, value modeling, pricing, forecasting, commercial negotiation, deployment, and expansion. The role translates AI, data, infrastructure, security, and governance capabilities into strategic business outcomes while navigating federated organizations and complex procurement processes.

Owns complex human data and annotation programs end to end, translating machine learning requirements into workflows, standards, and instructions. Manages distributed annotator teams, task allocation, training, performance, quality, throughput, timelines, reporting, and risk. Partners with Quality, Product, and Engineering teams to establish measurable acceptance criteria, improve processes, and resolve technical edge cases for AI and robotics projects.

Lead end-to-end architecture, implementation, and delivery of Blue Yonder Warehouse Management and related execution solutions. Serve as the primary client contact, manage timelines, budgets, risks, and deliverables, and lead solution teams and integrations. Provide functional and technical guidance, mentor junior staff, align solutions with business objectives, and collaborate with project managers, delivery partners, and stakeholders to deliver successful client outcomes.

Lead end-to-end data science and machine learning solutions for dynamic content targeting, from business conception through production deployment and impact evaluation. Partner with stakeholders, improve model quality and lifecycle processes, use model outputs to guide user experiences, and explore emerging AI techniques. The role requires advanced Python, SQL, dbt, statistical modeling, production ML deployment, and clear communication with technical and non-technical audiences.

Lead end-to-end AI and technology consulting engagements, from opportunity shaping and client advisory through delivery governance and team leadership. Design and deliver production-grade AI/ML, LLM, software, and cloud solutions, including agentic systems, MLOps, monitoring, cloud architecture, APIs, front-end applications, testing, security, and CI/CD. Apply deep technical expertise while communicating effectively with technical and non-technical stakeholders and supporting practice growth.

Engage qualified prospects interested in Benchmark Gensuite’s EHS, sustainability, ESG, risk, and operational excellence software. Conduct discovery conversations, deliver tailored product demonstrations, answer commercial questions, guide evaluations, and build stakeholder relationships through conversion. Collaborate with Marketing, Solution Consultants, Customer Success, Product, and sales teams while maintaining accurate Salesforce pipeline records. Represent the company at meetings, webinars, conferences, and industry events, with occasional UK and European travel.

Designs and delivers scalable modern big data platforms, including streaming, data lake, and lakehouse architectures. Advises senior client stakeholders on data strategies, cloud-native modernization, governance, analytics, and AI integration. Leads solution design, implementation, transformation initiatives, and technical collaboration across multiple sectors. Contributes thought leadership, reusable assets, and practice growth while aligning data platforms with measurable business outcomes.

Lead productionization and optimization of ML models for a global, serverless inference platform. Build benchmarking/evaluation tooling, improve inference performance (quantization, compilation, batching), integrate models with heterogeneous GPUs and accelerators, enhance deployment workflows and observability, and mentor engineers while driving ML production best practices.

Build, scale, and evolve Ki’s end-to-end MLOps system supporting underwriting, actuarial, rules-based, and machine learning models. The role improves production delivery speed and safety, promotes model management best practices, supports compliance, educates colleagues, identifies system enhancements, and mentors early-career team members. It requires collaboration across technical and commercial teams to advance digital underwriting capabilities.

Lead technical direction for complex data science and machine learning projects, design production-grade solutions, define roadmaps, manage technical risk, support sales engagements, advise customers, establish best practices, and mentor data scientists and cross-functional teams.

Lead the technical direction and delivery of complex machine learning and software projects. Architect scalable production systems, define roadmaps, manage high-risk workstreams, develop reusable libraries, mentor and hire engineers, evaluate technologies, estimate work, and advise customers and stakeholders. The role combines advanced software and ML engineering with team leadership, technical coaching, client delivery, and solution architecture.

Own technical relationships with enterprise and government customers across the Nordics. Design enterprise architectures, lead customer evaluations and pilots, demonstrate AI solutions, translate business needs into technical solutions, advise on best practices, gather product feedback, and collaborate with account executives, partners, Product, and Engineering teams to drive adoption and scale solutions architecture processes.

Lead strategic presales and value engineering for AI and data transformation opportunities. Facilitate executive discovery, quantify ROI and business value, shape solution hypotheses, create AI prototypes and demos, and support proposals, pricing, and deal closure. Partner with sales, delivery, architecture, marketing, and leadership to ensure solutions are compelling and feasible. Contribute thought leadership, reusable presales assets, client workshops, and market positioning around GenAI, agentic workflows, modern data platforms, and enterprise transformation.