201 to 225 of 272 MLOps Jobs in London

integrating with live data feeds and cloud infrastructure. Research and prototype cutting-edge AI techniques (e.g., deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data … BE CONSIDERED... Please apply directly by emailing jordanna.ramsey@searchability.com with your CV and availability. KEYWORDS: AI Engineer, Machine Learning Engineer, Sports Analytics, Computer Vision, Deep Learning, Python, TensorFlow, PyTorch, MLOps, Data Science, Predictive Modelling, Sports Tech, AI in Sports More ❯

of analytical tools, frameworks, and environments used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model … Qualifications • 6–10 years of experience in applied data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g. More ❯

of analytical tools, frameworks, and environments used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model … Qualifications • 6–10 years of experience in applied data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g. More ❯

CI/CD pipelines for data workflows and ensure lineage, observability, and compliance across environments. Collaborate with AI/ML teams to support model training, deployment, and monitoring using MLOps frameworks. Establish and enforce data governance policies, stewardship models, and metadata management practices Monitor and improve data quality using rule-based profiling, anomaly detection, and GenAI-powered automation Support GenAI … experience Data Quality:Ability to implement profiling, cleansing, standardization, and anomaly detection frameworks. Security & Compliance:Knowledge of data privacy, access control, and secure data exchange protocols. Defining and creating MLOPs pipeline Good to Have Skills GenAI Exposure:Experience with LLMs, LangChain, HuggingFace, synthetic data generation, and prompt engineering. Digital Twin Integration:Familiarity with nVidia Omniverse, AWS TwinMaker, Azure Digital Twin More ❯

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 … learning models to production Implement solutions to monitorthe performance of Machine Learning models in production over time Work in teams with other technical experts, e.g. Data Engineers, Data scientists, MLOps Engineers, Data Visualization Specialists Interact with domain experts from different industries to understand and tackle challenging problems Explore and understand client datain relation to the problem you're tackling andcommunicate More ❯

withdata manipulationusing libraries such asPandasandNumPy, and familiarity withparallelizationorasynchronous programming. Proficiency in Test-Driven Development (TDD) and an understanding of Python testing libraries such as Pytest. Cloud, CI/CD & MLOps Knowledge Experience taking models from experiments through to production deployments, with tools such as Docker, Kubernetes & serverless alternatives such as AWS Lambda. Familiarity with MLOps tools such as MLFlow, Kubeflow More ❯

of the chemical and energy supply chain. Build agent-based systems that perform complex automated tasks, updating the digital twin based on real-time data. Establish the foundations for MLOps and performance monitoring. Design and build robust, scalable ETL/ELT pipelines to ingest large volumes of data from APIs, web scraping, and multiple data sources. Own the scalability, reliability … technologies (AWS, Azure, or GCP). Expert knowledge of Python and SQL Hands-on experiences with Data Architecture, including: Cloud platforms and orchestration tools (e.g. Dagster, Airflow) AI/MLOps: Model deployment, monitoring, lifecycle management. Big Data Processing: Spark, Databricks, or similar. Bonus: Knowledge Graph engineering, graph databases, ontologies. Located in London And ideally you... Are a zero-to-one More ❯

of the chemical and energy supply chain. Build agent-based systems that perform complex automated tasks, updating the digital twin based on real-time data. Establish the foundations for MLOps and performance monitoring. Design and build robust, scalable ETL/ELT pipelines to ingest large volumes of data from APIs, web scraping, and multiple data sources. Own the scalability, reliability … technologies (AWS, Azure, or GCP). Expert knowledge of Python and SQL Hands-on experiences with Data Architecture, including: Cloud platforms and orchestration tools (e.g. Dagster, Airflow) AI/MLOps: Model deployment, monitoring, lifecycle management. Big Data Processing: Spark, Databricks, or similar. Bonus: Knowledge Graph engineering, graph databases, ontologies. Located in London And ideally you... Are a zero-to-one More ❯

hyper-personalise every shopper touchpoint. As we scale from research to production, we need robust infrastructure that makes our models reliable, reproducible, and observable at scale. As a Senior MLOps Engineer, you will own the infrastructure and tooling that turns experimental models into dependable production systems. You will build the pipelines, monitoring, and deployment workflows that allow our Research Engineers More ❯

hyper-personalise every shopper touchpoint. As we scale from research to production, we need robust infrastructure that makes our models reliable, reproducible, and observable at scale. As a Senior MLOps Engineer, you will own the infrastructure and tooling that turns experimental models into dependable production systems. You will build the pipelines, monitoring, and deployment workflows that allow our Research Engineers More ❯

Quantitative Developer – Trading – MLOps/Python A hedge fund is building out their AI capability and have an opportunity for a quantitative developer to play a key role in building out MLOps workflows and pipelines for the trading desks. This role is ideally suited to a software engineer or quantitative developer with experience delivery solutions directly for trading desks, who … has excellent Python skills, with a solid background in one of Java/C C#, who has experience building MLOPs pipelines for data scientists, AI engineers, quants, traders and leadership, to build strategic systems and enhance production systems. You should apply for this role if you are/have: 10+ years software engineering/quantitative development within financial markets Excellent … Python (NumPy, PyTorch, TensorFlow, Scikit); solid OO background in C++, Java or C# Strong MLOps and AI/ML model lifecycle experience Strong financial product knowledge and experience delivering solutions for trading/pricing Degree educated or higher in a relevant discipline from a leading academic institution This is an £800-900/day PAYE role based London initially for More ❯

Quantitative Developer – Trading – MLOps/Python A hedge fund is building out their AI capability and have an opportunity for a quantitative developer to play a key role in building out MLOps workflows and pipelines for the trading desks. This role is ideally suited to a software engineer or quantitative developer with experience delivery solutions directly for trading desks, who … has excellent Python skills, with a solid background in one of Java/C C#, who has experience building MLOPs pipelines for data scientists, AI engineers, quants, traders and leadership, to build strategic systems and enhance production systems. You should apply for this role if you are/have: 10+ years software engineering/quantitative development within financial markets Excellent … Python (NumPy, PyTorch, TensorFlow, Scikit); solid OO background in C++, Java or C# Strong MLOps and AI/ML model lifecycle experience Strong financial product knowledge and experience delivering solutions for trading/pricing Degree educated or higher in a relevant discipline from a leading academic institution This is an £800-900/day PAYE role based London initially for More ❯

ML platforms for enterprise-wide adoption. Lead deployment of LLM, RAG, and Generative AI systems at scale. Partner with business, data, and engineering teams to operationalize AI initiatives. Establish MLOps and LLMOps frameworks for lifecycle automation, compliance, and monitoring. Champion Responsible AI practices across all stages of development and deployment. What We’re Looking For ✅ 8+ years of experience in … Snowflake and MongoDB for data modeling and integration. ✅ Hands-on experience with Azure, AWS, or GCP cloud ecosystems. ✅ Deep proficiency in PyTorch, TensorFlow, or Scikit-learn . ✅ Understanding of MLOps, LLMOps , and modern data engineering best practices. Why Ascendion? At Ascendion, we combine human creativity and technology excellence to build the future of digital innovation. You’ll join a team More ❯

🚀 AI Engineer (LangGraph Expert) Salary: £90k - £130k + Equity + Bonus Location: Remote/Hybrid in London We’re looking for a brilliant AI Engineer who’s passionate about building intelligent, agentic systems using LangGraph. If you thrive at the More ❯

🚀 AI Engineer (LangGraph Expert) Salary: £90k - £130k + Equity + Bonus Location: Remote/Hybrid in London We’re looking for a brilliant AI Engineer who’s passionate about building intelligent, agentic systems using LangGraph. If you thrive at the More ❯

A global lifestyle brand is hiring a Data Scientist to join the team. You will report to the Director of Global Customer Data Science and work on developing predictive models and customer segmentation strategies to enhance personalised experiences and improve More ❯

A global lifestyle brand is hiring a Data Scientist to join the team. You will report to the Director of Global Customer Data Science and work on developing predictive models and customer segmentation strategies to enhance personalised experiences and improve More ❯

A global lifestyle brand is hiring a Data Scientist to help uncover insights from customer data and drive personalisation across the consumer journey. The role sits within the Consumer Intelligence and Experience (CIX) team, which leads market research, segmentation, and More ❯

pipelines using LLMs and transformer-based architectures. Analyse unstructured data, including medical text and images. Develop predictive models for underwriting decisions. Implement automated ML workflows, CI/CD, and MLOps practices. Architect APIs for model integration and external system interaction. Monitor performance to ensure scalable, reliable production deployments. What We’re Looking For: Essential: Experience with LLMs (GPT, BERT) and … for domain-specific applications. Strong Python skills (OOP, PyTorch, Hugging Face, scikit-learn, Pandas, NumPy). Deploying models with Docker, Kubernetes, or serverless platforms. Familiarity with CI/CD, MLOps, and cloud platforms (AWS preferred). Desirable: Named entity recognition, recommendation systems, or image analysis. Knowledge of Java (Spring Boot) or GitLab/GitHub CI/CD. Why Join? Lead More ❯

pipelines using LLMs and transformer-based architectures. Analyse unstructured data, including medical text and images. Develop predictive models for underwriting decisions. Implement automated ML workflows, CI/CD, and MLOps practices. Architect APIs for model integration and external system interaction. Monitor performance to ensure scalable, reliable production deployments. What We’re Looking For: Essential: Experience with LLMs (GPT, BERT) and … for domain-specific applications. Strong Python skills (OOP, PyTorch, Hugging Face, scikit-learn, Pandas, NumPy). Deploying models with Docker, Kubernetes, or serverless platforms. Familiarity with CI/CD, MLOps, and cloud platforms (AWS preferred). Desirable: Named entity recognition, recommendation systems, or image analysis. Knowledge of Java (Spring Boot) or GitLab/GitHub CI/CD. Why Join? Lead More ❯

LLM models; build LLM apps with LangChain/LangGraph; apply multimodal AI, prompt engineering, fine-tuning, and model optimization; ensure scalable, reliable, and business-aligned AI solutions. - Platform & Operations (MLOps): Deploy and operate services on Azure; implement CI/CD and Infrastructure as Code; add monitoring, logging, and observability; ensure reliability, fault tolerance, and performance optimization. - Governance & Security: Enforce data … integration skills. - Experience with ML/LLM frameworks (PyTorch, TensorFlow, scikit-learn, LangChain/LangGraph, LlamaIndex). - Familiarity with cloud deployment (Azure), CI/CD, Infrastructure as Code, and MLOps best practices. - Knowledge of databases, vector search, and knowledge graphs. - Understanding of security, compliance, and ethical AI. Personal Attributes: - Passionate, pragmatic, and self-driven with strong technical leadership. - Able to More ❯

LLM models; build LLM apps with LangChain/LangGraph; apply multimodal AI, prompt engineering, fine-tuning, and model optimization; ensure scalable, reliable, and business-aligned AI solutions. - Platform & Operations (MLOps): Deploy and operate services on Azure; implement CI/CD and Infrastructure as Code; add monitoring, logging, and observability; ensure reliability, fault tolerance, and performance optimization. - Governance & Security: Enforce data … integration skills. - Experience with ML/LLM frameworks (PyTorch, TensorFlow, scikit-learn, LangChain/LangGraph, LlamaIndex). - Familiarity with cloud deployment (Azure), CI/CD, Infrastructure as Code, and MLOps best practices. - Knowledge of databases, vector search, and knowledge graphs. - Understanding of security, compliance, and ethical AI. Personal Attributes: - Passionate, pragmatic, and self-driven with strong technical leadership. - Able to More ❯

Engineering & Semantic Search . Edge AI & Real-Time AI Deployments . Act as the architect and reviewer of AI systems, ensuring scalability, robustness, and compliance. Guide the adoption of MLOps best practices (CI/CD for ML, monitoring, retraining, governance). Drive innovation while balancing pragmatism and production readiness . Mentorship & Team Development Build and grow a world-class AI … architectural & practical) of: LLMs, RAG, and AI Agents . Predictive analytics & time-series forecasting . Computer vision, multimodal learning, and geospatial AI . Reinforcement learning and optimization techniques . MLOps practices & data pipelines . Ability to review code, design architectures, and guide technical teams . Advanced degree (Master’s or PhD is a plus) in Computer Science, AI, Data Science More ❯

Using frameworks like LangChain , PyTorch , and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker , or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/CD and model monitoring to cost and performance optimisation. Partnering with Data Engineers to ensure the pipelines and data structures feeding the models are …/ML or LLM-driven products. Experience with cloud ML platforms (AWS SageMaker, Bedrock, Vertex AI, etc.). Familiarity with LangChain or similar orchestration frameworks. A solid understanding of MLOps and how to take models from concept to production. A collaborative mindset - you enjoy working closely with Product and Data teams and mentoring others when needed. Curiosity, experimentation, and a More ❯

Using frameworks like LangChain , PyTorch , and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker , or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/CD and model monitoring to cost and performance optimisation. Partnering with Data Engineers to ensure the pipelines and data structures feeding the models are …/ML or LLM-driven products. Experience with cloud ML platforms (AWS SageMaker, Bedrock, Vertex AI, etc.). Familiarity with LangChain or similar orchestration frameworks. A solid understanding of MLOps and how to take models from concept to production. A collaborative mindset - you enjoy working closely with Product and Data teams and mentoring others when needed. Curiosity, experimentation, and a More ❯