Top Machine Learning Jobs in Manchester

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.

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 Sigmoid’s CPG Supply Chain Analytics consulting practice in Bengaluru by setting strategy, expanding market presence, driving revenue, developing go-to-market initiatives, overseeing advanced analytics solutions, advising clients, managing knowledge initiatives, and representing the company through thought leadership. The role requires strategic customer leadership, supply chain expertise, analytics solution experience, and the ability to lead teams and business growth.

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 develop scalable cloud-native data platforms, batch and streaming pipelines, data lakes, and ETL/ELT solutions. Support analytics and AI/ML workloads while implementing DevSecOps, Infrastructure as Code, and reliable data services. Collaborate with clients, architects, engineers, and consultants to solve complex data challenges across defence, government, and national security environments. The role requires strong Python, SQL, Spark, AWS, containerization, and distributed data processing expertise, plus current high-level security clearance and up to 80% onsite work.

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.

Own technical product marketing for Bloomreach’s APIs, integrations, and Loomi agentic AI platform. Develop positioning, use cases, partner launch strategies, go-to-market plans, customer messaging, sales enablement, and technical integration materials. Collaborate cross-functionally with Product, Engineering, Solutions Engineering, partners, sales, and enterprise stakeholders to translate complex platform capabilities into compelling customer value. Define launch metrics, evaluate outcomes, and communicate AI and data technologies clearly to technical audiences.

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.

Own the strategy, requirements, evaluation, and reliability of AI agent products. Partner with ML, backend, and mobile engineers to make trade-offs across quality, latency, cost, UX, and reliability. Define offline and online evaluation frameworks, incorporate human feedback, guide prioritization, and ensure AI features are understandable, predictable, safe, and trusted by users.

Own the end-to-end product strategy and execution for AI agent systems. Define technical and behavioral requirements, evaluate model performance, guide trade-offs across quality, latency, cost, reliability, and user experience, and partner closely with ML, backend, and mobile engineers. Establish evaluation frameworks, prioritize roadmaps, drive rapid and safe delivery, and ensure AI features are predictable, trustworthy, and valuable to users.

Lead platform product ownership bridging cloud and firmware strategy and execution. Manage and prioritize backlog, engage customers, collaborate with R&D, define releases, and drive agile delivery aligned with product leadership.

Own the Device Intelligence product roadmap for tier‑1 network service providers. Define PRDs, AI/LLM-assisted workflows, and technical requirements; lead discovery, backlog prioritization, and cross-functional delivery; engage strategic customers and support sales with competitive positioning.

Embed with engineering clients to own full-cycle technical hiring for software, AI/ML, infrastructure and data roles. Run deep intakes, headhunt passive candidates, coach hiring managers on interview design and calibration, build hiring foundations, report on pipeline health, and use/builder recruitment AI agents to scale impact.

Lead Rasa’s product organization and define strategy for its enterprise conversational AI platform. Manage and develop a team of product managers, own product roadmaps and lifecycle decisions, and partner with engineering, sales, and marketing on product definition, pricing, packaging, and go-to-market. Use customer research, market analysis, competitive intelligence, and developer feedback to guide innovation and foster a strong ecosystem across cloud, on-premises, and open-source deployments.

Design, implement, and optimize AI-powered solutions to support financial compliance and controls. Monitor GAAP/IFRS adherence, automate controls and reporting, support internal/external audits, and manage complex accounting areas like revenue recognition and lease accounting while collaborating with finance, audit, and technology teams.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

The role involves building infrastructure for training open source foundation models, with emphasis on autonomy and contributing in a dynamic team.

As a P&C Actuary, you will assess insurance risks, review regulatory compliance, support audit teams, and document findings while nurturing client relationships and contributing to practice development efforts.

Leads global AI quality, accreditation, and conformity assessment activities, including obtaining EU AI Notified Body designation, developing regulatory processes, and ensuring consistent certification practices. The role advises internal teams and customers, represents BSI in international technical forums, establishes competency criteria, supports regulatory programs, identifies process improvements, and shapes the AI and machine learning business strategy. It requires expertise in global AI regulations, quality management, legislation, technical product areas, stakeholder influence, and people leadership.

Lead and operationalize a company-wide AI governance program: build frameworks, assess AI risks and use cases, embed controls in SDLC, run governance council, liaise with Siemens consortium, handle regulatory compliance (EU AI Act, NIST AI RMF), produce reporting, and deliver training and documentation across Product, Engineering, Legal, Privacy, HR and Security.

The role involves embedding in various parts of the business to identify and solve AI problems, producing working solutions through short sprints, and evaluating their effectiveness while facilitating adoption.

As a Software Engineering Intern, you will contribute to building features for user-facing products, APIs, and scalable services for machine learning. Responsibilities include crafting code, designing data pipelines, implementing tools, and enhancing technical documentation.