2,276 to 2,300 of 2,754 Machine Learning Jobs in London

equivalent research/industry experience Demonstrable hands-on experience building and deploying document understanding systems, information extraction pipelines, or knowledge graph construction using deep learning, LLMs and NLP methods Proven ability to translate complex document understanding problems into innovative AI applications that balance accuracy and efficiency Professional experience scaling … efficiency optimization including knowledge distillation, model compression, and designing SLM-based solutions that balance performance with computational constraints Solid understanding of DL/ML approaches used for NLP tasks Experience designing annotation workflows, creating high-quality labeled datasets with clear guidelines, and developing evaluation frameworks for document understanding tasks #LI ...

permanent talent and contractors. Mentorship: Coach existing team members through process updates and modern cross-functional ways of working. Skills & Qualifications Data Science & ML Expertise: Strong academic background (e.g., Master’s degree in Data Science or a scientific discipline with significant ML focus) alongside practical data science experience. Software Engineering ...

Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration Transformational Impact: Guide strategic customers as they implement transformational big data projects, including end-to-end design, build and deployment … with distributed computing with Apache Spark and knowledge of Spark runtime internals Familiarity with CI/CD for production deployments Working knowledge of MLOps, ML/AI models and AI APIs Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/ ...

Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment … with distributed computing with Apache SparkTM and knowledge of Spark runtime internals Familiarity with CI/CD for production deployments Working knowledge of MLOps, ML/AI models and AI APIs Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/ ...

with Bachelor's degree in computer science or a related discipline, or equivalent work experience required; advanced degree preferredStrong hands-on experience with Python, ML frameworks, and LLM/GenAI tooling. Strong hands-on experience with AI Development tools like Claude CLI, WindsurfSolid understanding of the ML lifecycle; exposure ...

Bachelor's degree in computer science or a related discipline, or equivalent work experience required; advanced degree preferred Strong hands-on experience with Python, ML frameworks, and LLM/GenAI tooling. Strong hands-on experience with AI Development tools like Claude CLI, Windsurf Solid understanding of the ML lifecycle; exposure ...

Bachelor's degree in computer science or a related discipline, or equivalent work experience required advanced degree preferred Strong hands-on experience with Python, ML frameworks, and LLM/GenAI tooling. Strong hands-on experience with AI Development tools like Claude CLI, Windsurf Solid understanding of the ML lifecycle exposure ...

with leading technology providers such as Microsoft, Snowflake, Databricks, and Collibra. What sets us apart is how we build capabilities and careers. Through continuous learning, real-world experience, and a collaborative culture, we help our people develop the skills, confidence, and experience to build rewarding careers. What … understanding of regulatory, ethical, accuracy and security considerations for developing autonomous agentic systems (Desirable): Degree, Masters or Doctorate in Software Engineering, Computer Science or ML/AI related subject Benefits 33 days annual leave (25 days annual leave plus 8 public holidays) Pension matching up to 5% Unlimited mental health ...

from technical scoping and architecture design through production launch. Cross-Functional GenAI Alignment: Drive execution and manage complex technical dependencies across systems engineering, Core ML, Research, and Product teams to deliver unified SGP capabilities with architectural consistency. Technical Translation & Requirements: Translate complex infrastructure metrics (LLM inference optimization, GPU utilization, compute … proven track record of having built and shipped technical products or platforms from scratch (e.g., internal cloud infrastructure, developer APIs, distributed systems, or ML platforms).Platform Domain Expertise: 3+ years of dedicated experience managing programs focused directly on core engineering infrastructure, cloud-native ecosystems (AWS/GCP), container orchestration (Kubernetes ...

collaboratively to share skill sets and solve problems. At Methods we have fun while working hard; we are not afraid of making mistakes and learning from them. Predominantly focused on the public-sector, Methods is now building a significant private sector client portfolio. Methods was acquired by the Alten … organisations. Experience developing data strategies, AI strategies, transformation roadmaps, business cases or investment cases. Strong understanding of Data & AI capabilities, including analytics, AI/ML, GenAI, data platforms, data governance, architecture and adoption considerations. Experience prioritising use cases based on value, feasibility, risk, organisational readiness and strategic alignment. Experience working ...

Nice to Have: Familiarity with Data Mesh or Lakehouse architectures. Familiarity with Kubernetes, Docker, and real-time streaming technologies (e.g. Kafka, Kinesis).Exposure to ML engineering pipelines or MLOps frameworks. What's it like to work at Zego? At Zego, we operate like a high-performing sports team. We come … buildPrivate medical insurance, for you and your familyPension, generous holiday, and 1,000 a year to spend on getting to the office or learning something newCutting-edge systems and tools, so you always have what you need to drive your impactIf you're ready to help build the real ...

intelligent systems are built and delivered at JPMorganChase. In this role, you’ll contribute to the LLM Suite platform by building AI/ML and agentic capabilities that are secure, reliable, and ready for production. You’ll collaborate closely with senior engineers, learn through real design discussions, and grow your … in. As a Software Engineer, Senior Associate, in the LLM Suite Engineering team, you will design, build, and troubleshoot software that enables AI/ML and agentic experiences on the platform. You will write secure, high-quality code and support algorithms that integrate with existing systems. You will collaborate with ...

curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth … multi-year initiatives that span business and technology across enterprise customersPreferred qualifications Deep expertise in Generative AI, Agentic AI, or cloud-native AI/ML solutions Agentic Platform (AgentCore & Bedrock), AI SDLC (Kiro & AI Migrations), and Business Productivity (Quick). Experience orchestrating cross-functional delivery teams (consulting, engineering, partners) from ...

supportive and collaborative tech community through knowledge-sharing and peer-level support, coaching and mentoring Deepen your expertise through our a culture of learning and growth – you'll have budget to take courses (technical and non-technical training), plus gain certifications Job DescriptionAs a Data Architect you will help … ensure scalable, high-performance applications: Multi-cloud, data warehousing and data lake platforms Data manipulation, integration and ingestion technologies Programming/scripting languages ML/AI frameworks Infrastructure & DevOps concepts and tooling, iData Visualization/BI & Analytics platforms, Semantic models and metrics layers Data governance tooling As a Principal Consultant ...

valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen … regulatory controls, and with vulnerability patching across base OS images, networking and IAM Experience with Bazel, Nix and other similar technologies Experience serving ML models in production, or building data and real-time analysis pipelines Experience working on projects related to national security for one or more government agencies Prior ...

Document complex technical architectures clearly and articulate system requirements, post‐mortems, and engineering strategies effectively to both technical and non‐technical stakeholders. AI/ML Platform Automation : Architect and maintain highly available MLOps platforms across AWS and Azure environments. Developer Enablement : Build self‐service infrastructure tools, deployment templates, and continuous … this is the place for you. Qualifications Platform Experience : Demonstrable DevOps experience, with a proven focus on building software engineering platforms or AI/ML infrastructure. IaC Mastery : The successful candidate must demonstrate advanced proficiency in Infrastructure as Code (IaC), with a track record of building and maintaining complex cloud ...

Document complex technical architectures clearly and articulate system requirements, post-mortems, and engineering strategies effectively to both technical and non-technical stakeholders. AI/ML Platform Automation : Architect and maintain highly available MLOps platforms across AWS and Azure environments. Developer Enablement : Build self-service infrastructure tools, deployment templates, and continuous … place for you. Skills, Experience & Personal Attributes Platform Experience : Demonstrable DevOps experience, with a proven focus on building software engineering platforms or AI/ML infrastructure. IaC Mastery : The successful candidate must demonstrate advanced proficiency in Infrastructure as Code (IaC), with a track record of building and maintaining complex cloud ...

first designDevOps: CI/CD (GitHub Actions, Jenkins), Terraform, containerization (Docker/Kubernetes)Orchestration - : Airflow, Step Functions, BPM toolsObservability (desirable): GrafanaAI (desirable): AI/ML or GenAI adoption for automation and operational efficiencyExperience & SkillsProven experience as a Solutions Architect/Senior Technical Lead in complex enterprise environments. Strong track record … secure systems. Strong understanding of risk management, controls, and regulatory environments. Experience operating in matrix organizations with multiple stakeholders. Experience with AI/ML or intelligent automation use casesWhat We're Looking ForHands-on mindset – willing to dive into technical detail when neededAbility to balance ideal architecture with real-world ...

behaviour, investment, sales and performance. Embed privacy, security, consent, retention and cross-border data requirements into the architecture from the outset. Define how analytics, ML, AI services and agents access structured data safely and consistently. Produce data models, flows, lineage, architecture decision records and reusable design patterns for engineering … ideally including dbt. Experience with consumer, digital and transactional data at scale, including web and app analytics and GA4. Understanding of data design for ML, AI or automated decisioning, including trusted definitions, controlled access and decision/outcome capture. Knowledge of privacy and security by design across multiple jurisdictions, including ...

behaviour, investment, sales and performance. Embed privacy, security, consent, retention and cross-border data requirements into the architecture from the outset. Define how analytics, ML, AI services and agents access structured data safely and consistently. Produce data models, flows, lineage, architecture decision records and reusable design patterns for engineering … ideally including dbt. Experience with consumer, digital and transactional data at scale, including web and app analytics and GA4. Understanding of data design for ML, AI or automated decisioning, including trusted definitions, controlled access and decision/outcome capture. Knowledge of privacy and security by design across multiple jurisdictions, including ...

behaviour, investment, sales and performance. Embed privacy, security, consent, retention and cross-border data requirements into the architecture from the outset. Define how analytics, ML, AI services and agents access structured data safely and consistently. Produce data models, flows, lineage, architecture decision records and reusable design patterns for engineering … ideally including dbt. Experience with consumer, digital and transactional data at scale, including web and app analytics and GA4. Understanding of data design for ML, AI or automated decisioning, including trusted definitions, controlled access and decision/outcome capture. Knowledge of privacy and security by design across multiple jurisdictions, including ...

Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialisation in one area (e.g. real-time/streaming, ML/AI, data governance, migrations)Proven ability to lead architecture discussions with senior technical stakeholders: whiteboarding, design reviews, and trade-off analysisTrack record of driving platform adoption … Computer Science, Engineering, or a quantitative discipline (or equivalent experience)Willingness to travel up to 30% as neededNice to Have: Databricks certifications (Data Engineer, ML, Platform)Cloud provider certifications at professional level (e.g. AWS Certified Solutions Architect – Professional or AWS Certified Data Engineer; Azure Solutions Architect Expert; Google Professional Cloud ...

credential handling for external and internal integrations. Build end-to-end data flows from source through governed ingestion and curated layers to BI, ML or application consumption. Required Hands-on Technical Skills Deep hands-on Azure Databricks implementation and troubleshooting Databricks Serverless and compute/workload optimisation Azure identity, networking … RStudio migration or consolidation experience. Migration of analytical/data science workloads (convert and migrate R development/Libraries to Databricks). AI/ML, LLM integration, model lifecycle, RAG/vector retrieval or model-serving experience. Large-scale enterprise platform transformation and regulated-industry experience. Strong cost optimisation ...

credential handling for external and internal integrations. Build end-to-end data flows from source through governed ingestion and curated layers to BI, ML or application consumption. Required Hands-on Technical Skills Deep hands-on Azure Databricks implementation and troubleshooting Databricks Serverless and compute/workload optimisation Azure identity, networking … RStudio migration or consolidation experience. Migration of analytical/data science workloads (convert and migrate R development/Libraries to Databricks). AI/ML, LLM integration, model lifecycle, RAG/vector retrieval or model-serving experience. Large-scale enterprise platform transformation and regulated-industry experience. Strong cost optimisation ...

Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialisation in one area (e.g. real-time/streaming, ML/AI, data governance, migrations) Proven ability to lead architecture discussions with senior technical stakeholders: whiteboarding, design reviews, and trade-off analysis Track record of driving platform … Science, Engineering, or a quantitative discipline (or equivalent experience) Willingness to travel up to 30% as needed Nice to Have Databricks certifications (Data Engineer, ML, Platform) Cloud provider certifications at professional level (e.g. AWS Certified Solutions Architect – Professional or AWS Certified Data Engineer; Azure Solutions Architect Expert; Google Professional Cloud ...