201 to 225 of 3,213 Machine Learning Jobs in the UK

working within Agile delivery environments. Desirable Experience Databricks certifications. Kafka or Structured Streaming. CI/CD and DevOps practices. Docker and Kubernetes. Exposure to Machine Learning pipelines. Experience within Financial Services or other highly regulated environments. About You You'll be an experienced Data Engineer or Technical Lead ...

capabilities, and skills Practical experience delivering system design, application development, testing, and operational stability at enterprise scale Experience designing and deploying production AI/ML systems, including LLM-based applications and agentic architectures in regulated environments Proficiency in one or more programming languages, particularly Python and/or PySpark Advanced … knowledge of software application development and technical processes in disciplines such as cloud, AI/ML, or data engineering Experience in large-scale data processing, microservices, API design, and orchestration frameworks Working knowledge of relational and NoSQL databases, vector stores, and data lake architectures Familiarity with observability tools and frameworks ...

software engineering experience, with strong fundamentals in system design, data structures, and clean code practices. Proven experience designing and shipping production-grade AI or ML-enabled software systems. Strong proficiency in Python, including building and shipping production backend services. Hands‐on experience building applications with LLMs such as Azure OpenAI … monitoring. Experience implementing responsible AI practices in a regulated environment, including audit trails, confidence scoring, and human‐in‐the‐loop controls. Background in traditional ML or data engineering, including feature pipelines, model training, and ETL, is preferred. MongoDB or other NoSQL database experience is preferred. Prior exposure to insurance domain ...

ecosystems using Azure, AWS or GCP Data strategy, operating models and transformation roadmaps Data governance, data quality and wider data management initiatives AI and machine learning use cases that support business growth and innovation Programme governance, planning, risk management and delivery activities Cross-functional teams including Architects, Engineers ...

security. Strong understanding of DevOps, CI/CD, and modern software development methodologies. Demonstrated experience with Agentic AI systems, autonomous agents, and advanced machine learning frameworks. Extensive hands-on experience with message-based technologies such as Apache Kafka and AMPS, including design, deployment, and optimization. Advanced proficiency ...

work relates to that. Take ownership of the system produced. Contribute to a strong team sense of identity and spirit. Foster a learning culture within the team. Work within best practices for secure, compliant, and reliable systems. Essential 5+ years experience in software engineering Professional understanding of agile concepts … Familiarity with messaging systems such as Kafka, RabbitMQ or similar Proficiency with monitoring tools like Prometheus, Grafana, or ELK Stack Experience with AI/ML integration in backend systems. Why Join Us At Lockwood, you’ll be part of an inclusive, creative, and highly motivated team. You’ll work ...

Architecture capabilities: Master and Reference Data Management, Data Quality, Metadata Management, Data Taxonomy, Data Integration, Data Migration, and Data Modeling. Demonstrated proficiency in AI, machine learning, or related techniques as applied to architecture or software engineering disciplines. Hands‐on experience with object‐oriented software development using languages such ...

with the ability to work hands-on where required. Experience designing integrations across multiple enterprise platforms, APIs and external data sources. Knowledge of AI, machine learning or Large Language Model use cases within operational environments. Ability to operate across strategy, architecture and delivery while remaining pragmatic and outcome ...

Advanced knowledge of software applications and technical processes with considerable in‐depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Ability to tackle design and functionality problems independently with little to no oversight Experience in Computer Science, Computer Engineering, Mathematics ...

expanding its team and looking to bring in several Machine Learning Engineers . You'll help design and deploy data pipelines, ML models, and production systems that deliver real-time insights and automation throughout the business. This role is ideal for someone with strong software engineering fundamentals, hands … data experience, and a passion for building scalable, high-quality ML and data solutions in production environments. Essential Experience Strong programming skills in Python (Pandas, NumPy, etc.). Proficiency in SQL for data querying and transformation. Hands-on experience with Machine Learning techniques and frameworks (e.g., scikit-learn ...

skills for querying relational databases. Experience using AI-assisted coding and workflow tools to support reproducible data analysis, with appropriate human review Experience applying machine-learning methods to text classification, named entity recognition, or information extraction Experience with Git/GitHub/GitLab Experience with cloud platforms, especially ...

line of code, but you understand the platform end-to-end and own outcomes. You'll partner closely with product owners, data scientists and machine learning engineers, site reliability engineering, and business stakeholders to deliver stable, scalable cloud-native analytics. Job responsibilities Own application governance and records ...

agentic workflows that tie it all together. You will partner with computational chemists, CADD scientists, software engineers, and hardware engineers, and apply AI/ML to build the next generation of Chemify's platform. What sets this role apart is the combination of breadth of ML problems — generative chemistry, vision … search, agents — paired with a robotic platform that turns your models into physical experiments. If working across a wide range of hard ML problems on a real-world platform sounds like the right shape of job for you, we'd love to welcome you to our team. Key Responsibilities Build ...

infrastructure automation Background in enterprise software, SaaS platforms, or technically demanding application domains (scientific computing, real‐time systems, large‐scale data) Exposure to integrating machine learning, generative AI, or LLM‐based components into application features Experience mentoring less experienced engineers Energy industry experience is not required ...

skills for querying relational databases. Experience using AI‐assisted coding and workflow tools to support reproducible data analysis, with appropriate human review Experience applying machine‐learning methods to text classification, named entity recognition, or information extraction Experience with Git/GitHub/GitLab Experience with cloud platforms, especially ...

artefacts (templates, examples, checklists) that support effective adoption of recommended practices.* Lead and facilitate the AI engineering knowledge and community activities—curating content, running learning sessions, and integrating feedback into improved guidance.* Review and adapt industry best practices, working with internal experts to publish reusable patterns and architectural recommendations.B … Experience applying software engineering fundamentals: writing tests, structuring user stories, managing iterative releases, and working with CI/CD pipelines.* Experience in AI/ML, software, or platform engineering, with exposure to automated testing and infrastructure‐as‐code or policy‐as‐code.* Working knowledge of AI observability (logs, metrics, traces ...

Demonstrated experience building and deploying AI, data, software or platform products in enterprise or customer environments. Experience with foundation models, large language models, machine learning models or multimodal AI applications. Familiarity with AI agents, retrieval-augmented generation, embeddings, vector databases, semantic search, model APIs or orchestration frameworks. Understanding ...

infrastructure automation Background in technically complex or scientifically demanding application domains (distributed systems, scientific computing, real-time systems, large-scale data) Experience integrating machine learning, generative AI, or LLM-based components into production systems Experience contributing to open-source projects, or integrating open-source components at scale. Energy ...

fine‐tuning, tailored to diverse product requirements. You will design and build production‐grade inference systems, working across Swift, Java, and Python to integrate ML capabilities seamlessly into Apple's ecosystem. As a senior technical contributor, you will set engineering standards, mentor engineers, and influence the technical roadmap for generative … features, taking full ownership from problem definition and prototyping through production release, working across Swift, Java, and Python codebases Establish engineering excellence across the ML development lifecycle, including robust testing, reproducibility, monitoring, documentation, and CI/CD for model and data pipelines Partner with research, product, design, and platform teams ...

Machine Learning Engineer at Autodesk Research, you will work side-by-side with researchers and engineers to build and enable ML-powered capabilities in Autodesk products. You are an ML engineer with strong software engineering skills who is passionate about solving problems and building things, and excited … offices in London. Responsibilities Collaborate on projects at the intersection of research and product with a diverse, global team Build and iterate on ML pipelines, prototypes, and evaluation workflows, enabling rapid deployment and testing of experimental models Work with complex datasets and representations for model training, evaluation, and analysis Analyze ...

ability to detect financial crime, prevent fraud, and safeguard our customers. Working closely with data scientists and engineers, you will focus on developing scalable ML pipelines, agentic AI systems, production‐grade model code, and robust monitoring systems. You will play a key role across the full machine learning … frameworks (e.g., Spark). Experience with deep learning/NLP frameworks (e.g., PyTorch, Hugging Face). Solid understanding of software engineering principles and ML lifecycle practices (MLOps/LLMOps). Previous experience owning and delivering ML projects, including stakeholder management. Additional Highly Valued Skills Experience leading machine learning ...

beyond proof of concept into secure, production-grade deployment. The role: - Design AI and GenAI architecture strategies and roadmaps - Build scalable AI/ML and Agentic AI platforms - Work across LLMs, RAG, embeddings and semantic search - Support AI deployment, governance and integration patterns - Collaborate with engineering, data, DevOps and business … Vector databases MLOps/LLMOps AWS/Azure/GCP/Databricks Kubernetes & GPU infrastructure What you'll bring: - Experience designing enterprise AI or ML architectures - Strong grasp of cloud and modern data platforms - Exposure to scalable AI deployment and integration patterns - Financial Services or regulated industry experience (essential) - Strong ...

Solution Architects through to senior technical leadership. What you'll be doing Designing AI and GenAI architecture strategies and roadmaps Building scalable AI/ML and Agentic AI platforms Working across LLMs, RAG, embeddings and semantic search Supporting AI deployment, governance and integration patterns Collaborating with engineering, data, DevOps … frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise AI or ML architectures Strong understanding of cloud and modern data platforms Exposure to scalable AI deployment and integration patterns Financial Services or regulated industry experience essential Strong ...

Solution Architects through to senior technical leadership. What you'll be doing Designing AI and GenAI architecture strategies and roadmaps Building scalable AI/ML and Agentic AI platforms Working across LLMs, RAG, embeddings and semantic search Supporting AI deployment, governance and integration patterns Collaborating with engineering, data, DevOps … frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise AI or ML architectures Strong understanding of cloud and modern data platforms Exposure to scalable AI deployment and integration patterns Financial Services or regulated industry experience essential Strong ...

wide goals Drive architectural decisions and technical excellence across teams Ensure robust systems for deployment, monitoring, scalability, and reliability of infrastructure supporting AI/ML workloads Collaborate with engineering leaders globally to align on technical standards, best practices, and cross-site initiatives Team Building & Talent: Build and scale high-performing … office Deep technical expertise in distributed systems, cloud platforms (AWS, GCP, or Azure), and infrastructure automation Experience with infrastructure supporting large-scale AI/ML systems, including: GPU infrastructure and orchestration ML training and inference pipelines Model serving and deployment at scale Strong understanding of modern infrastructure technologies: Kubernetes, Terraform ...