476 to 500 of 6,120 Machine Learning Jobs in the UK

Software Engineer – AI Enabled Engineering · UK We are seeking a skilled Java Software Engineer with a growing interest and demonstrated exposure to AI/ML integration. This role is primarily Java-centric — you will design and build cloud-native microservices on our BPA (Beyond Policy Administration) platform — with the expectation … leading global insurers and reinsurers. A collaborative, innovation-driven culture with exposure to modern technologies and cloud-native architectures. Professional development opportunities, certifications, and learning programs. Competitive compensation and benefits package, aligned with experience and location. #J-18808-Ljbffr ...

model governance practices, including clear documentation, version control and validation protocols. Drive process improvement by evaluating new technologies and methodologies, including artificial intelligence and machine learning, and support product development and market research through data analysis and quantitative modelling. Collaborate with Enterprise Technology, Information Technology and Investment Risk ...

coaching engineers on safe, compliant adoption within delivery practicesDemonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.). Practical experience in cloud computing. Knowledge of network protocols and technologies such as TCP/IP, DNS, DHCP ...

prompting. An understanding of point in time data is a strong plus Also desirable: experience with vector databases (pgvector, Pinecone, Weaviate, Qdrant or similar); machine learning experience (PyTorch, TensorFlow, XGBoost/LightGBM) for building, maintaining and extending existing models; Bloomberg API integration to Python; data science/statistics ...

relentlessly resourceful to solve problems and find smarter solutions than the status quo Build the best technology in-house, using new data sources, machine learning and AI to make machines do the heavy lifting We’re looking for a full-stack Python engineer to join our Central Operations ...

deliver analytical products that directly shape football decisions. Support our R&D team in the design and implementation of world-leading statistical and machine learning models, drawing insight from football datasets including event data, optical and broadcast tracking data, and GPS/performance data. Effectively utilise AI coding ...

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 ...

solutions involve custom engineering of unique solutions and experiences created from modern web-scale technologies, such as HTML5, JavaScript, Micro-Services, Cloud Computing and Machine Learning. As a technology specialist, EY offers you the opportunity to apply your skills in a highly strategic context, working on meaningful and impactful … hands-on delivery with technical leadership, mentorship, and ownership of complex systems. We are looking for someone who is ready to challenge themselves by learning new technologies, lead developer teams and understand a product from end to end. Your key responsibilitiesActively participate and own the design, development and delivery ...

have the following characteristics, it would be a plus. Advanced degree (MSc/PhD) in a quantitative or clinical discipline. Hands‐on experience with machine learning techniques applied to operational or time‐to‐event problems. Familiarity with clinical trial systems and data (e.g., EDC, IRT/IXR, CTMS ...

work collaboratively in a team environment. Ability to communicate complex ideas effectively, both verbally and in writing A strong software engineering background with machine learning expertise to understand how the user facing product will tie into backend and architectural decisions Nice to Have Experience with FHIR ...

model governance practices, including clear documentation, version control and validation protocols. Drive process improvement by evaluating new technologies and methodologies, including artificial intelligence and machine learning, and support product development and market research through data analysis and quantitative modelling. Collaborate with Enterprise Technology, Information Technology and Investment Risk ...

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 ...

protocols (OAuth2, OpenID Connect, TLS, etc.). Experience integrating legacy banking systems with modern digital platforms. Experience integrating data platforms used for analytics or machine learning. Familiarity with real-time vs batch data patterns and their impact on analytical and AI use cases. Awareness of AI model lifecycle considerations … insurance Various policies to support your mental wellbeing, including a robust behavioural health network with counselling and coaching services Access a wide range of learning and development opportunities and career progression opportunities Ambitious remuneration package We recognise our role as a bank to support social change and welcome ...

teams and documenting technical solutions. A proactive, self‐motivated approach to addressing issues and driving improvements in backend systems. A strong commitment to continuous learning and staying up‐to‐date with emerging technologies and industry best practices. Nice-to-Have Qualifications: Familiarity with message brokers such as Kafka … tools like Jira for managing tasks and sprint planning. Certifications in cloud technologies, such as AWS Certified Developer. Manage, host, and serve AI/ML models (MLOps), by ensuring their scalability, reliability, and performance in production environments. Location: Candidates based in Spain: flexible remote work, with availability to travel ...

across UK, US and Hyderabad teams. Create a culture of experimentation, pace, quality and responsible AI delivery. You Have: Significant experience in applied AI, machine learning, data science, analytics engineering, automation or AI-enabled transformation. Strong understanding of generative AI, LLMs, RAG, agents, workflow automation, prompt engineering, evaluation ...

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 ...

have the following characteristics, it would be a plus- Advanced degree (MSc/PhD) in a quantitative or clinical discipline.- Hands-on experience with machine learning techniques applied to operational or time-to-event problems.- Familiarity with clinical trial systems and data (e.g., EDC, IRT/IXR, CTMS ...

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 … model from our offices in London. ResponsibilitiesCollaborate on projects at the intersection of research and product with a diverse, global teamBuild and iterate on ML pipelines, prototypes, and evaluation workflows, enabling rapid deployment and testing of experimental modelsWork with complex datasets and representations for model training, evaluation, and analysisAnalyze errors ...

based sequence encoders, temporal survival models, gradient-boosted decision trees) that predict key vulnerabilities in housing, health, and other social domains. Track developments in ML and frontier models, running structured experiments to bring promising techniques into production safely. Build robust evaluation pipelines, training datasets, and model infrastructure to support continuous … degree in Computer Science, Machine Learning, or a related technical field – or equivalent practical experience. 3+ years of professional experience as an ML Engineer, or related role. Strong programming skills and production experience in Python. Experience building and maintaining data or ML pipelines with an orchestration tool such ...

real-world problems in finance. For nearly two decades, we have led our industry and worked at the frontier of applying AI/ML to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future.Your colleagues will include internationally recognized experts … ability to collaborate effectively with researchers whose primary expertise is not software engineering Preferred Qualifications Experience with experiment management, model evaluation pipelines, or ML workflow orchestration Familiarity with modern ML/AI infrastructure patterns (model serving, feature stores, distributed training) Experience with performance profiling and optimization of numerical or modeling ...

Python engineer who has some exposure to AI development or AI-enabled applications . You do not need to be an AI/ML specialist; the priority is excellent core Python engineering skills combined with an interest in applying AI technologies to real-world solutions. Previous experience within banking … back‐end applications, services and APIs. Previous exposure to AI development, AI-enabled applications or AI-related PoCs . Understanding of how AI/ML capabilities can be integrated into software applications. Experience working with RESTful APIs and microservices architectures. Strong SQL skills and experience working with relational databases such ...

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 ...

transform the way biomedical professionals carry out their research and day‐to‐day exploration. What you’ll be doing Design and implement ML/AI solutions end‐to‐end, from the idea and data exploration phase to deployment and monitoring, balancing cutting‐edge techniques with pragmatism to deliver measurable impact. … reliable, maintainable, production‐ready and can be readily adapted to future developments. Choose the right approach for the problem at hand, evaluating classical ML and NLP techniques, LLM‐based solutions, and agentic solutions to balance trade‐offs between speed, cost, complexity, interpretability, and performance. Collaborate closely with product, design ...

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/ ...