326 to 350 of 4,926 Machine Learning Jobs in England

catalyst for accountable growth, not a brake. What We Are Looking For Engineering & Technical Leadership Substantial experience leading software engineering, data, or AI/ML teams, typically 12+ years of relevant experience with several in a leadership capacity, delivering production-grade solutions at enterprise scale. Strong hands‐on foundations … example Python, SQL, cloud‐native platforms, data pipelines), enough to set technical direction credibly and make sound architecture decisions. Demonstrated experience with AI/ML technologies, including LLMs, Retrieval Augmented Generation (RAG), agentic workflows, Natural Language Processing (NLP), and predictive analytics, and the discipline to run them reliably in production. ...

data science, statistical modelling, or large-scale data analysis. Experience developing front-office applications, automation frameworks, or other business-critical software. Experience building AI, machine learning, or LLM-based solutions. Familiarity with financial markets, electronic trading systems, Equities, ETFs, Delta One products, distributed systems, or KDB+/q. ...

e.g. Snowflake, Redshift, etc.) and also IaC (e.g. Terraform, CloudFormation) Pragmatic approach to solving problems Nice to haves Keen interest in modern AI/ML techniques Experience in a consultancy or client-facing role Certifications in relevant technologies (e.g. AWS Cloud Practitioner, Azure Fundamentals, etc.) Why Indicium AI Plentiful opportunity … support for learning & development; £2k annual training budget (with 5 study days), access to Udemy, external consulting & leadership skills training Fast-growing start-up organisation with huge opportunity for career growth Competitive salary package along with company annual bonus A hugely collaborative working environment where every person’s viewpoint ...

instruments. Required Qualifications, Capabilities, and Skills Enrolled in a Master’s program in mathematics, statistics, physics, engineering, computer science, economics, or data science/machine learning, graduating between September 2026 andMarch2028. Proficiencyin Python, and/or C++ programming. Strong modeling, analytical, quantitative, and problem-solving skills. Excellent communication ...

principles, enhancing the programmability, efficiency, and resilience of network operations. Mentor and guide engineering teams, provide technical leadership and foster a culture of continuous learning and professional growth. Serve as a technical authority, advising stakeholders on network architecture, emerging technologies, and industry best practices. This role can be based … fault detection, Root cause analysis, Dynamic RF optimisation, Automated channel selection, Automated power adjustments, Client steering, Service assurance automation, Network anomaly detection Experience leveraging machine learning and analytics to improve user experience, wireless performance, service availability and operational resilience. Ability to define architectures that support autonomous network operations ...

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 ...

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 ...

issues in a simple way. Team player, interested in sharing knowledge and helping to develop the team. Skills in data science, predictive modelling & analytics, machine learning, AI Required Education Qualified actuary (FIA) or holder of an equivalent qualification from a recognised actuarial professional body. Excellent academic qualifications including ...

marketing effectiveness programs for international clients, from data strategy and collection to modelling, insights, and activation. Apply econometrics, regression, Bayesian statistics, and machine learning methods to analyse marketing and customer data. Collaborate closely with Managers to understand the project scope, structure, analytical approaches, manage operations and ensure timely ...

quality. Working knowledge of Python or another programming language for analysis. Familiarity with Git, version control and modern analytics workflows. Good understanding of AI, machine learning concepts and their practical application. Ability to mentor others and raise the quality of analytical work across a team. Knowledge of music ...

make better decisions, faster. Customers rely on Databricks for the full range of data workloads, including data engineering, ETL, near real-time streaming, machine learning, SQL analytics, and advanced analytics. The Solutions Architect (EDW Migrations) executes on Databricks’ strategic product lines to develop, establish and drive product adoption ...

Strong communication skills for cross-team collaboration Proactive approach to system reliability and performance optimization Continuous learning mindset in rapidly evolving AI/ML landscape Balance of practical engineering rigor with innovative solution development Life @ Crypto.com Empowered to think big. Try new opportunities while working with a talented, ambitious ...

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 ...

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 ...

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 ...

Purpose: you can use your passion and abilities at Leidos to keep the people you care about safe. We are at the forefront of machine learning, AI, cyber security and solutions. Using your skills in the technology frontline by helping to build a safer world. You can inspire ...

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 ...

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 ...

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/ ...