2,301 to 2,325 of 2,743 Machine Learning Jobs in London

infrastructure, and administering Kubernetes clusters across multi-region AWS environments. You'll work alongside experienced and passionate engineers who enjoy solving tough challenges and learning from one another. This is a hands-on team Lead role where you will balance technical expertise with team leadership. Elliptic is building … resilience through SLOs, error budgets, and chaos engineering. Working knowledge of LLM-based services and AI infrastructure. You don't need to be an ML engineer, but you should be comfortable deploying, securing, and operating AI Gateways and services (e.g. Kong AI Gateway, LangGraph deployments, or similar)You'll Thrive ...

predictive signals. Building world-class research tooling to speed up Algo Developers' research iteration. Aiding the development and deployment of very large deep learning models for HRT's live trading. Improving HRT's monetization systems which turn our predictions into profitable trades. Evaluating sim vs. live differences to improve … superlative reviews. Experience with supporting internal users is preferred; bonus if you have real hands-on experience with quant research and/or ML/Deep Learning platforms. Experience with python numerical, ML and data-oriented libraries is a big plus (e.g. pandas, scikit, pytorch, etc.)Candidates should ...

pragmatic resolution of validation events/failures, ensuring required records are maintained. Maintain awareness in developments in Artificial Intelligence (AI) and Machine Leaning (ML), including Generative AI, Agentic AI and Large Language Models (LLM) and their use in the development of IXICO computerized systems and products/services. Ensure … Excellent knowledge and experience of Information Security requirements & controls (ISO 27001/SOC2). Knowledge of SaMD regulatory requirements, including the integration of AI & ML into SaMD. Self-starter, organised with a character aligned to IXICO’s core values of Accountability, Ability, Agility and Aspiration. Excellent Microsoft Office package experience ...

work and finding a balance between perfection and practicality. FTI's AI build team is technology-agnostic with software engineering expertise to deploy advanced ML/AI methodologies at scale. Our engagements include using NLP for automated document classification, geospatial modeling of electric vehicle demand, demand forecasting, predictive maintenance, price … simultaneously managing smaller projects or workstreams on larger projects. You will showcase your expertise across a number of technical areas including programming, AI/ML and best practices. What You'll DoData ManagementDevelop and oversee comprehensive ETL processesDesign and maintain functional relational databasesStructure and perform quality control procedures for data ...

work and finding a balance between perfection and practicality. FTI's AI build team is technology-agnostic with software engineering expertise to deploy advanced ML/AI methodologies at scale. Our engagements include using NLP for automated document classification, geospatial modeling of electric vehicle demand, demand forecasting, predictive maintenance, price … including strong knowledge of database structure and efficiency. Proficiency in the following version control language: GitProficiency in any of the following AI/ML frameworks: Huggingface, Torch, Tensforflow, Scikit-Learn, and SpacyExperience in of any of the following additional platforms related to MLOps: MLFlow, dbt, Docker, Kubernetes. Experience with working ...

work and finding a balance between perfection and practicality.FTI's AI build team is technology-agnostic with software engineering expertise to deploy advanced ML/AI methodologies at scale. Our engagements include using NLP for automated document classification, geospatial modeling of electric vehicle demand, demand forecasting, predictive maintenance, price optimization … including strong knowledge of database structure and efficiency.* Proficiency in the following version control language: Git* Proficiency in any of the following AI/ML frameworks: Huggingface, Torch, Tensforflow, Scikit-Learn, and Spacy* Experience in of any of the following additional platforms related to MLOps: MLFlow, dbt, Docker, Kubernetes.* Experience ...

strong external perspective that informs Dynatrace’s internal strategy.What will help you succeedMinimum Requirements12+ years of progressive experience in enterprise technology, AI/ML, or digital transformation leadership — with at least 3–5 years in a senior director or equivalent role with demonstrated portfolio ownership.Preferred RequirementsDemonstrated success shaping and operationalizing … hours offer you the flexibility you need.AI-driven workflowsUse AI as your daily teammate to automate tasks and focus on what matters.Learn & developCompany-wide learning perks, designated team's learning days, and more.Volunteering dayA day of paid volunteer time to support a community or cause you care about.Regular ...

agile team that designs, builds, and operates the services that make large language models usable at scale. This is an infrastructure-meets-ML role: you don't need to be an ML researcher, but you should be excited to learn how model architectures and inference constraints translate into real production ...

shaping the future of fintech – and we're just getting started. There are a myriad of opportunities to use AI/ML as part of business processes in checkout, and we're looking for an expert to help us make these a reality. Unlike many such roles, this … opportunity to truly drive innovation at scale that matters. We're looking for a Staff Level AL/ML engineer to accelerate our adoption into the AI era; helping us set our AI vision and show us what is possible. As part of the Data and AI platform team ...

Leveraged AI‐assistive development tools for tasks like scaffolding, refactoring, debugging, test generation, and documentation Experience building or integrating AI/ML‐powered features into products or systems (e.g., recommendation engines, NLP models, computer vision, predictive analytics) Used context‐appropriate automated testing to inform software design choices and catch bugs … balance technology choices while delivering high‐quality work within deadlines Leading architecture and software design discussions Collaborating on systems that involve the full ML lifecycle from data ingestion and preprocessing, to model deployment, integration, and performance monitoring Generating new potential solutions to challenges (technical and non‐technical) in partnership with ...

role in our Global AI & Data Science team to design, develop and deploy data science models across Marketing, Commercial and Digital, delivering impactful ML solutions. You will collaborate with product owners, data engineers and ML engineers, write production code, define metrics, and contribute to responsible AI governance and model deployment. … strong academic background (MS or PhD) with Python, R and SQL, plus hands-on ML experience with frameworks such as #J-18808-Ljbffr ...

case studies, and reference accounts. Qualification 5–10+ years in Customer Success, Technical Account Management, or related enterprise‐facing roles, ideally in AI/ML infrastructure, cloud computing, or deep‐tech hardware or software. Demonstrated ability to manage complex, multi‐stakeholder accounts and build executive‐level relationships with technical … business audiences. Working knowledge of AI/ML workflows, large language models (LLMs), or HPC infrastructure — enough to credibly engage with data science and ML engineering teams. Proven track record of driving adoption, retention, and expansion within a technical enterprise product. Excellent project management skills with the ability to manage ...

teamsAI & Data (Practical, Not Theoretical)Hands‐on experience with: LLMs and modern AI toolingRAG systems, embeddings, vector searchAgentic patterns (tools, planners, evaluators)Experience productionising ML/AI systems (monitoring, failure modes, iteration)Pragmatic mindset: understands where AI adds value — and where it doesn'tWays of WorkingAgent‐first, spec‐driven … engineersBias toward shipping, learning, and iteratingNice to Have (But Not Required)Experience with logistics, optimization, or simulation‐heavy domainsBackground in data engineering or ML platformsExperience building developer tools or internal platformsExposure to regulated or security‐conscious environmentsTech StackBackend: Python (Django/FastAPI), TypeScript (Node.js)Frontend: ReactAI: LLMs, RAG pipelines ...

product infrastructure that support education product features and platform experiencesMove quickly from prototype to production, balancing speed, quality, maintainability, and user impactIntegrate and productize ML/AI solutions in close collaboration with digital experience and platform engineering teamsBuild and maintain automation, plugins or SDKs for CAD platforms (e.g., Fusion, Revit … participate actively in code reviews and design discussions; follow security and data-handling best practicesCollaborate closely with product managers, designers, researchers, frontend engineers, ML engineers, and platform teams to turn ambiguous problems into shipped featuresDocument designs, APIs, runbooks and hand-off materials to product teams, and help onboard other engineers ...

customer obsession and technical excellence. A key dimension of this role is helping customers understand how AWS foundational services underpin and enable AI/ML transformation — ensuring infrastructure readiness, performance optimization, and security posture as customers scale their AI ambitions. Key Job Responsibilities Team Leadership & Management Build, coach, and retain … domain areas Identify patterns in customer needs across the region to inform product priorities, especially at the intersection of core infrastructure and AI/ML workloads Represent AWS in executive-level discussions, public speaking engagements, industry events, and written content that demonstrates how AWS infrastructure delivers customer value Basic Qualifications ...

Platform Engineer to build and own the infrastructure that underpins our AI-driven materials discovery platform. You'll work directly with world-renowned ML researchers and software engineers to accelerate real scientific breakthroughs by making model training, experimentation, and deployment fast, reliable, and reproducible. This is a foundational hire. … configuration, job scheduling, and cost optimisation. Build and maintain CI/CD pipelines that support rapid model iteration, automated testing, and safe deployments. Support ML workflow orchestration; experiment tracking, training run management, and data pipeline reliability. Ensure reproducibility across research and production environments through containerisation and rigorous environment management. Define ...

design and review infrastructure, and your instinct for security and reliability makes the whole platform better.* You unblock people. Data engineers, ML engineers, and Data teams depend on the platform to move fast. You’re the person who understands what they need, builds the right foundations, and makes sure … across the organisation* Operate and evolve GCP data platform services - BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub - in close collaboration with data and ML engineering teams* Support IAM, service account design, and security posture across the platform, enforcing least-privilege principles* Lead incident response and root cause analysis ...

client, a leading global SaaS organisation is looking for a Senior Data Analyst to work on exciting AI/ML user experience projects for a 12 month contract. Hybrid with 3 days on site. Responsibilities; Providing data sources that help build the AI/ML user experience Build and maintain ...

client, a leading global SaaS organisation is looking for a Senior Data Analyst to work on exciting AI/ML user experience projects for a 12 month contract. Hybrid with 3 days on site. Responsibilities; Providing data sources that help build the AI/ML user experience Build and maintain ...

intelligent automation solutions—from discovery through to delivery and optimisation. Technical & Domain Expertise Hands‐on experience with Intelligent Automation technologies (e.g., RPA, AI/ML, NLP, IDP). Knowledge of on‐premise and cloud architectures. Understanding of business analysis methods such as BPMN and DMN. Awareness of RTA legislation … automation within sustainability topics. Experience developing technical capabilities within teams Design solutions across IDP, NLP, ML, RPA, workflow orchestration, and low‐code platforms. Assess client automation maturity and shape strategic roadmaps. Create compelling G2M materials and C‐Suite‐level packs, alongside detailed solution architecture. Technical Tools & Platforms Experience with ...

skills with the ability to influence cross-functional teams. Strong communication and presentation skills, including engagement with senior business stakeholders. Knowledge of AI/ML capabilities, customer data ecosystems, and modern data platforms. Ability to interpret data and customer insights to drive product decisions and business outcomes. Demonstrated experience delivering … such as Snowflake, Azure Data Lake, or similar cloud-based technologies. Understanding of model monitoring, observability, and performance tracking practices. Exposure to AI/ML-enabled products and data monetization initiatives. Rewards & Benefits TCS is consistently voted a Top Employer in the UK and globally. Our competitive salary packages feature ...

that incorporate GenAI and LLM platforms for example Claude, OpenAI, Gemini or equivalent alongside agent orchestration and tool use and design scalable AI and ML solutions aligned to business goals, integrating them into existing enterprise landscapes, and embed appropriate LLMOps controls, evaluation and Responsible AI Governance. Strategy, operating model … first‐class services we are known for. Please note that with all of our roles, you should expect some in‐person time for collaboration, learning and building relationships with clients, peers, leaders and communities. As an employer, we will be as flexible as possible to support your specific work ...

work on the entire company's backend code base: data models, algorithms, data pipelines, infrastructure, APIs, complex database queries, LLM agent pipelines, ML models. Deploy, manage and support on-premise deployments of Circuit Mind’s software. Learn, use, and improve best practices and processes for high-quality software development. … days a week in the office. 5 weeks per year to work wherever you want in the world. London Bridge office. Extended parental leave. Learning and development budget to support your professional development. Yearly retreat. Access to Circuit Mind's cutting edge EDA platform. At Circuit Mind we value ...

someone who can drive innovation while delivering under tight timelines and high expectations. The role You will lead multidisciplinary engineering teams (AI/ML, data, software, platform) to deliver AI capabilities that are trusted, adopted, and production-grade . You’ll partner with senior stakeholders & Product Managers to define outcomes … Lead engineering execution across multiple teams, ensuring clear ownership boundaries, interfaces, and ways of working Drive pragmatic technical direction across AI systems: LLM/ML deployment patterns, model lifecycle, monitoring, and iteration Ensure production readiness: security, reliability, observability, governance, and cost awareness (FinOps mindset) Unblock teams through active problem-solving ...

enterprise architecture, technical consulting, or technical pre-sales in Data and AI domains.Deep, hands-on technical expertise across enterprise data platforms, AI/ML, Generative AI, and agentic architectures — including Salesforce Agentforce, Data360, and the Salesforce platform.Demonstrated experience engaging C-level executives (CDO, CTO, CIO, CDAO) as a trusted technical … with hyperscalers vs. Salesforce. Deep familiarity with Informatica (IDMC) for enterprise data integration and MDM, alongside Snowflake, Databricks, BigQuery, and Redshift.AI & Agentic Architecture Foundational ML concepts, data preparation, Python, applied AI, Generative AI, prompt engineering, retrieval-augmented generation (RAG), vector stores, and agentic architectures. Hands-on familiarity with platforms like ...