676 to 700 of 3,667 Machine Learning Jobs in England

distributed systems, microservices architecture, and event-driven patterns. Demonstrated experience with real-time applications and data streaming technologies (e.g., WebSockets, gRPC, Kafka). Experience integrating third-party AI/ML APIs (e.g., LLMs, STT/TTS, or other complex services) into production systems. Experience with containerization (Docker, Kubernetes) and deploying/managing services on a major cloud platform (AWS, GCP More ❯

distributed systems, microservices architecture, and event-driven patterns. Demonstrated experience with real-time applications and data streaming technologies (e.g., WebSockets, gRPC, Kafka). Experience integrating third-party AI/ML APIs (e.g., LLMs, STT/TTS, or other complex services) into production systems. Experience with containerization (Docker, Kubernetes) and deploying/managing services on a major cloud platform (AWS, GCP More ❯

distributed systems, microservices architecture, and event-driven patterns. Demonstrated experience with real-time applications and data streaming technologies (e.g., WebSockets, gRPC, Kafka). Experience integrating third-party AI/ML APIs (e.g., LLMs, STT/TTS, or other complex services) into production systems. Experience with containerization (Docker, Kubernetes) and deploying/managing services on a major cloud platform (AWS, GCP More ❯

distributed systems, microservices architecture, and event-driven patterns. Demonstrated experience with real-time applications and data streaming technologies (e.g., WebSockets, gRPC, Kafka). Experience integrating third-party AI/ML APIs (e.g., LLMs, STT/TTS, or other complex services) into production systems. Experience with containerization (Docker, Kubernetes) and deploying/managing services on a major cloud platform (AWS, GCP More ❯

distributed systems, microservices architecture, and event-driven patterns. Demonstrated experience with Real Time applications and data streaming technologies (eg, WebSockets, gRPC, Kafka). Experience integrating third-party AI/ML APIs (eg, LLMs, STT/TTS, or other complex services) into production systems. Experience with containerization (Docker, Kubernetes) and deploying/managing services on a major cloud platform (AWS, GCP More ❯

distributed systems, microservices architecture, and event-driven patterns. Demonstrated experience with real-time applications and data streaming technologies (e.g., WebSockets, gRPC, Kafka). Experience integrating third-party AI/ML APIs (e.g., LLMs, STT/TTS, or other complex services) into production systems. Experience with containerization (Docker, Kubernetes) and deploying/managing services on a major cloud platform (AWS, GCP More ❯

distributed systems, microservices architecture, and event-driven patterns. Demonstrated experience with real-time applications and data streaming technologies (e.g., WebSockets, gRPC, Kafka). Experience integrating third-party AI/ML APIs (e.g., LLMs, STT/TTS, or other complex services) into production systems. Experience with containerization (Docker, Kubernetes) and deploying/managing services on a major cloud platform (AWS, GCP More ❯

in leading AI or digital transformation projects, ideally in manufacturing or FMCG. Practical experience with AI tools like ChatGPT, Microsoft Copilot, and predictive analytics platforms. Familiarity with AI/ML frameworks (e.g., OpenAI API, TensorFlow, PyTorch) and automation platforms. Strong understanding of data integration, APIs, and enterprise architecture. Ability to translate business challenges into scalable technical solutions. Project management expertise More ❯

ML & Cloud Infrastructure Engineer Up to £180,000 London (Hybrid, 3/4/5 days onsite per week) Company: Early stage start up building the world’s first 3D Foundation Model, enabling generative capabilities in fully dynamic 3D environments, with motion, physics, and spatial reasoning built-in. Their mission is to redefine how industries, from robotics and AR/… VR to gaming and movies, generate and interact with 3D content. Responsibilities: Develop high-performance, cloud-based systems for ML training and API serving Manage and optimize infrastructure on AWS, GCP, or Azure; support local and distributed ML workflows Configure servers, monitor performance, and optimize storage for large-scale ML data Use Docker, Kubernetes, and Terraform to deploy and scale … applications Collaborate with researchers and engineers to streamline ML operations Handle incidents, troubleshoot issues, and improve system robustness Requirements: MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. 3 years professional experience in a cloud-related role, preferred ML-related. Strong coding skills in Python and SQL Proficiency in cloud platforms Proficiency in containerization Proficiency More ❯

learn, a mastery of our discipline, strong mathematical and statistical skills, and software engineering prowess. We typically specialise in fields such as Computer Vision, LLMs and Deep Learning. Our Machine Learning Engineers are responsible for all aspects of the AI lifecycle, from understanding business problems, preparing training data, assisting the data scientists in designing and building models, and … you will work collaboratively with Data Scientists, Software Engineers, Product and Engagement Managers on your designated project. You will not only work on the development and productionisation of sophisticated ML products, but also shape the future of our AI capabilities. You will have the opportunity to mentor junior team members, influence strategic decisions, and directly impact our customers' experiences. If … learning algorithms Support with customer PoVs and onboarding Understand business problems and product requirements and help translate these into technical solutions Execute and deliver full AI/ML solutions from sourcing training data, design and implementing state-of-the-art machine learning models, testing, benchmark and product-driven research for model performance improvement, to shipping stable More ❯

ML & Cloud Infrastructure Engineer Up to £180,000 London (Hybrid, 3/4/5 days onsite per week) Company: Early stage start up building the world’s first 3D Foundation Model, enabling generative capabilities in fully dynamic 3D environments, with motion, physics, and spatial reasoning built-in. Their mission is to redefine how industries, from robotics and AR/… VR to gaming and movies, generate and interact with 3D content. Responsibilities: Develop high-performance, cloud-based systems for ML training and API serving Manage and optimize infrastructure on AWS, GCP, or Azure; support local and distributed ML workflows Configure servers, monitor performance, and optimize storage for large-scale ML data Use Docker, Kubernetes, and Terraform to deploy and scale … applications Collaborate with researchers and engineers to streamline ML operations Handle incidents, troubleshoot issues, and improve system robustness Requirements: MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. 3 years professional experience in a cloud-related role, preferred ML-related. Strong coding skills in Python and SQL Proficiency in cloud platforms Proficiency in containerization Proficiency More ❯

Our client, a leading multi-strategy hedge fund managing over $20 billion of AUM, is seeking a Senior ML Engineer to join their high-performing Applied AI team, driving a new era of intelligent systems that underpin the organisations most critical decision-making. You will be developing production-grade AI systems that empower portfolio managers, analysts, and researchers with intelligent … LLMs and leveraging expertise in Knowledge Graphs and Graph Databases (Neo4j preferred). Responsibilities: Design and build intelligent data retrieval systems that power AI-driven investment tools. Collaborate with ML researchers to prototype, develop, and deploy new AI/ML products. Work with frontend engineers to integrate backend systems into user-facing applications. Lead architectural decisions and contribute to the … to a culture of technical excellence. Support critical infrastructure through on-call rotations and incident response. Requirements: 10+ years of professional software engineering experience, with 4+ years focused on ML systems Must have expertise in Knowledge Graphs and Graph Databases (Neo4j preferred) Advanced proficiency in Python, including ML libraries (e.g., PyTorch, scikit-learn) Strong experience with distributed systems, data engineering More ❯

Machine Learning/AI Engineer - Agentic Systems London Welcome to the video first world From your everyday PowerPoint presentations to Hollywood movies, AI will transform the way we create and consume content. Today, people want to watch and listen, not read - both at home and at work. If you're reading this and nodding, check out our brand … including Accel, Nvidia, Kleiner Perkins, Google and top founders and operators including Stripe, Datadog, Miro, Webflow, and Facebook. What you'll do at Synthesia: We are looking for a Machine Learning/AI Software Engineer who is passionate about building intelligent, scalable, and production-ready AI agents that redefine how people learn. You will join our Copilot Team … a background in Computer Science, Software Engineering, or a related field . You have 6+ years of experience in software engineering with at least 3+ years of experience in ML/AI engineering or NLP-related software development. You are an engineer at heart, you enjoy building working systems more than writing research papers. You have strong Python skills and More ❯

PRA SS1/23. The ideal candidate will have a strong quantitative background, hands-on programming experience in Python, and a track record of developing or validating AI/machine learning or statistical models in surveillance or conduct risk contexts. Key Responsibilities Independently validate and periodically review trade surveillance models for robustness and regulatory compliance Evaluate data quality … across surveillance systems Review model documentation for conceptual soundness, implementation quality, and governance controls Conduct benchmarking, backtesting, and stress testing using Python to challenge model design Assess statistical and machine learning-based surveillance systems for transparency and effective alert thresholds Provide quantitative and qualitative assessments of model accuracy, stability, and business suitability Collaborate with model developers, compliance, and … senior stakeholders Support regulatory validation work under FCA and other relevant frameworks Contribute to the enhancement of validation methodologies for surveillance models Skills and Experience Experience in data science, machine learning development or validation, or a quantitative role in financial services or regulated industries Strong academic background in data science, statistics, mathematics, computer science, or a related field More ❯

PRA SS1/23. The ideal candidate will have a strong quantitative background, hands-on programming experience in Python, and a track record of developing or validating AI/machine learning or statistical models in surveillance or conduct risk contexts. Key Responsibilities Independently validate and periodically review trade surveillance models for robustness and regulatory compliance Evaluate data quality … across surveillance systems Review model documentation for conceptual soundness, implementation quality, and governance controls Conduct benchmarking, backtesting, and stress testing using Python to challenge model design Assess statistical and machine learning-based surveillance systems for transparency and effective alert thresholds Provide quantitative and qualitative assessments of model accuracy, stability, and business suitability Collaborate with model developers, compliance, and … senior stakeholders Support regulatory validation work under FCA and other relevant frameworks Contribute to the enhancement of validation methodologies for surveillance models Skills and Experience Experience in data science, machine learning development or validation, or a quantitative role in financial services or regulated industries Strong academic background in data science, statistics, mathematics, computer science, or a related field More ❯

AI and Machine LearningEngineer About Data Reply: DATA REPLY are data specialists, offering data platforms, BI, advanced analytics and AI/Machine Learning (ML) solutions to drive business success. We specialise in developing, deploying and operating production data solutions on AWS cloud. Role overview: As a AI & Machine Learning Engineer, you'll be instrumental inthe … design and development of machine learningprocesses in a variety of client environments. You will analyse client requirements and help generate suitable recommendations. You will help managethe ML lifecycle fromdata selection and collection, ML model design and creation all the way through tooperationalizationand monitoring. You will work closely with data scientists and senior MLOps Engineers to understand and implement models … into production. At Data Reply, you'll enjoy extensive training opportunities coupled with a detailed learning pathto guide you along the way.You'll thrive in our diverse and vibrant work environment andwill be surrounded bypeerswho share your passion fordata and technology. As a graduate at Reply, you will get involved inHackathons, Code Challenges or Labcamps as well as our More ❯

Responsibilities Build and productionise Machine Learning models across asset classes. Apply advanced techniques in Machine Learning, statistics, and applied mathematics using Python (PyTorch or similar). Utilise cloud platforms like AWS SageMaker for fast scalability. Develop quantitative models to optimise trading, pricing, and risk management. Collaborate with sales teams to address client needs and develop solutions. … Maintain and support front office analytical libraries. Drive innovation through expertise in methodologies and industry advancements. Essential Skills Master's degree in STEM (PhD preferred). Strong foundation in Machine Learning, data science, and software engineering. Proven ability to create rigorous and practical solutions. Collaborative mindset and passion for learning and improvement. Experience mentoring, managing projects, and More ❯

deployment. Around 7 years' experience as a Software Engineer or Machine Learning Engineer. A strong grounding in Python, with hands-on experience building and shipping AI/ML or LLM-driven products. Experience with cloud ML platforms (AWS SageMaker, Bedrock, Vertex AI, etc.). A collaborative mindset - you enjoy working closely with Product and Data teams and mentoring More ❯

Erskine — with the expectation to attend any of these offices when required. Project Description: We are seeking a highly experienced Data Scientist with deep expertise in Python and advanced machine learning techniques. You need to have a strong background in statistical analysis, big data platforms, and cloud integration, and you will be responsible for designing and deploying scalable … Implement MLOps practices, including CI/CD, model monitoring, and lifecycle management. Mentor junior data scientists and contribute to team knowledge-sharing. Stay current with trends in AI/ML and data science. Mandatory Skills Description: Minimum 8+ years of hands-on experience in Data Science with strong expertise in Python and libraries such as Pandas, NumPy, SciPy, Scikit-learn … analysts, leading projects, and contributing to knowledge-sharing across teams. Continuous learner with strong problem-solving, communication, and leadership skills, staying updated with the latest trends in AI/ML and data science. More ❯

Data Science Engineer - MLOPS, Machine Learning, AI, Artificial Intelligence, Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL We are actively working with a global law firm who are actively looking to bolster their IT team as they undergo a global-scale cloud transformation. At present they are looking to take on a new Data Science Engineer (MLOPS … Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL) role, it's ideal you have: Ideal but not required law firm experience 2-4 years experience within AI/ML positions Knowledge of cloud platforms (Ideally Azure) AI/ML Frameworks Generative AI Data engineering knowledge Solution Delivery Design, build, and deploy data science and AI solutions end-to-end … testing, release, monitoring, and support. Operationalize models with CI/CD pipelines, automated testing, and monitoring, applying MLOps practices such as versioning, retraining, and drift detection (tools: MLflow, Azure ML, Databricks) Leverage both open-source frameworks (LangChain, Hugging Face, etc.) and enterprise platforms (Azure OpenAI, Databricks, etc.) to deliver production ready, scalable AI solutions Implement generative AI and advanced analytics More ❯

Senior Data Scientist Ai ML Python MML Japanese & English Speaking Working Pattern: Hybrid (12 days per week in office) Location: London The Data Science function plays a pivotal role in delivering advanced Artificial Intelligence capabilities across the organisation. This position focuses on designing, developing, and deploying production-grade machine learning solutions while contributing to the strategic growth of … team and collaborate closely with Software Engineers, Product Managers, and other stakeholders. The role requires strong mathematical and statistical foundations, excellent software engineering skills, and proven expertise in modern machine learning techniques, including Computer Vision, Natural Language Processing … and Deep Learning. ---------------------------------------- Key Responsibilities Design, build, and deploy advanced machine learning models and algorithms into production. Lead technical development within cross-functional teams, providing guidance on ML solution design and implementation. Translate business problems into clearly defined data science solutions and deliver end-to-end ML pipelines. Support proof-of-value initiatives and contribute to product roadmap More ❯

Lead the design and deployment of next-generation AI systems across Generative AI, Computer Vision, Forecasting, and Optimisation. Build and lead a world-class team of data scientists and ML engineers, setting technical direction and best practices across the company. Oversee the full AI lifecycle from experimentation and model development to robust ML deployment on Azure. Explore cutting-edge approaches … Proven track record leading AI or data science teams in production supply chain or logistics environments. Deep expertise in Computer Vision and Generative AI, with strong understanding of modern ML architectures, model training, and deployment techniques. 7+ years’ experience in applied ML, data science, or AI, including senior or leadership roles. Expert in Python, proficient with frameworks such as PyTorch … TensorFlow, FastAI, and experience with scikit-learn, MLflow, or ONNX. Solid engineering background—experienced in deploying and maintaining ML systems on Azure, including Azure Machine Learning, Azure Functions, Databricks, Docker, and Kubernetes. Experience with real-time data pipelines and streaming data using tools such as Kafka or Azure Event Hubs is a plus. Advanced degree (Master’s or More ❯

Lead the design and deployment of next-generation AI systems across Generative AI, Computer Vision, Forecasting, and Optimisation. Build and lead a world-class team of data scientists and ML engineers, setting technical direction and best practices across the company. Oversee the full AI lifecycle from experimentation and model development to robust ML deployment on Azure. Explore cutting-edge approaches … Proven track record leading AI or data science teams in production supply chain or logistics environments. Deep expertise in Computer Vision and Generative AI, with strong understanding of modern ML architectures, model training, and deployment techniques. 7+ years’ experience in applied ML, data science, or AI, including senior or leadership roles. Expert in Python, proficient with frameworks such as PyTorch … TensorFlow, FastAI, and experience with scikit-learn, MLflow, or ONNX. Solid engineering background—experienced in deploying and maintaining ML systems on Azure, including Azure Machine Learning, Azure Functions, Databricks, Docker, and Kubernetes. Experience with real-time data pipelines and streaming data using tools such as Kafka or Azure Event Hubs is a plus. Advanced degree (Master’s or More ❯

Lead the design and deployment of next-generation AI systems across Generative AI, Computer Vision, Forecasting, and Optimisation. Build and lead a world-class team of data scientists and ML engineers, setting technical direction and best practices across the company. Oversee the full AI lifecycle from experimentation and model development to robust ML deployment on Azure. Explore cutting-edge approaches … Proven track record leading AI or data science teams in production supply chain or logistics environments. Deep expertise in Computer Vision and Generative AI, with strong understanding of modern ML architectures, model training, and deployment techniques. 7+ years’ experience in applied ML, data science, or AI, including senior or leadership roles. Expert in Python, proficient with frameworks such as PyTorch … TensorFlow, FastAI, and experience with scikit-learn, MLflow, or ONNX. Solid engineering background—experienced in deploying and maintaining ML systems on Azure, including Azure Machine Learning, Azure Functions, Databricks, Docker, and Kubernetes. Experience with real-time data pipelines and streaming data using tools such as Kafka or Azure Event Hubs is a plus. Advanced degree (Master’s or More ❯

Lead the design and deployment of next-generation AI systems across Generative AI, Computer Vision, Forecasting, and Optimisation. Build and lead a world-class team of data scientists and ML engineers, setting technical direction and best practices across the company. Oversee the full AI lifecycle from experimentation and model development to robust ML deployment on Azure. Explore cutting-edge approaches … Proven track record leading AI or data science teams in production supply chain or logistics environments. Deep expertise in Computer Vision and Generative AI, with strong understanding of modern ML architectures, model training, and deployment techniques. 7+ years’ experience in applied ML, data science, or AI, including senior or leadership roles. Expert in Python, proficient with frameworks such as PyTorch … TensorFlow, FastAI, and experience with scikit-learn, MLflow, or ONNX. Solid engineering background—experienced in deploying and maintaining ML systems on Azure, including Azure Machine Learning, Azure Functions, Databricks, Docker, and Kubernetes. Experience with real-time data pipelines and streaming data using tools such as Kafka or Azure Event Hubs is a plus. Advanced degree (Master’s or More ❯