201 to 225 of 336 MLOps Jobs in the UK

AWS) Experience with RASTER Strong experience across industries in both Geospatial and non-Geospatial domains Experience with Machine Learning (sci-kit learn, tensorflow, metaflow, MLOps) Preferred Experience: Knowledge of Rust Experience with frameworks like Metaflow, Prefect, etc. Experience with geospatial libraries i.e. Raster, Geo-pandas, Vector databases This role would More ❯

AWS) Experience with RASTER Strong experience across industries in both Geospatial and non-Geospatial domains Experience with Machine Learning (sci-kit learn, tensorflow, metaflow, MLOps) Preferred Experience: Knowledge of Rust Experience with frameworks like Metaflow, Prefect, etc. Experience with geospatial libraries i.e. Raster, Geo-pandas, Vector databases This role would More ❯

development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations. Experience with developing and deploying Machine Learning Operations (MLOps) at scale. Experience with large scale foundational models and transformer-based architecture (GenAI). Immigration support: The company provides support for your immigration process to More ❯

teams and delivering complex software platforms and AI-native products. Deep expertise in Generative AI, Deep Learning, Reinforcement Learning, ML fundamentals, end-to-end MLOps, AI infrastructure, and proficiency with frameworks like PyTorch. Active interest and experience in multi-agent systems, collective learning, AI safety, secure agent execution, emerging AI More ❯

models: you have a detailed knowledge of the different delivery and deployment methodologies for data teams, such as agile data product development, AI/MLOps and AnalyticsOps. You will be able to align these methodologies with our clients' objectives and organisational structure, ensuring data teams can be as effective and More ❯

collaborate with a highly skilled team of engineers and data scientists to develop scalable ML models and deploy them into production environments using modern MLOps practices. If you're excited about solving real-world optimization problems, building high-performance ML infrastructure, and working with autonomous agent simulations, this is your … learning models, with a strong focus on reinforcement learning (RL) and multi-agent systems to optimize fleet behavior in dynamic environments. Implement and improve MLOps pipelines to support continuous training, deployment, monitoring, and scaling of machine learning models in production. Collaborate with data engineers and software developers to ensure seamless … programming skills, with a strong emphasis on writing efficient, scalable, and maintainable code. Proven experience with TensorFlow/PyTorch/Jax, Scikit-learn, and MLOps workflows for training, deployment, and monitoring of ML models. Experience working with Polars and/or Pandas for high-performance data processing. Proficiency with cloud More ❯

and behavioural intelligence models. Lead the transition of prototypes into scalable, cloud-native production systems. Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps). Work with large-scale time series and behavioural data from diverse sensors. Contribute to strategic technical decisions and mentor junior engineers. Collaborate cross-functionally … as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. A background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data More ❯

in AI, Data Engineering, and Architecture. You will lead the development of scalable, AI-driven solutions, combining deep technical knowledge of AWS Cloud Services, MLOps, and core Data Science concepts with proven leadership and strong technical project management capabilities. You will act as both a technical and project leader, ensuring … Management and Architects. Oversee the end-to-end lifecycle of AI projects including data ingestion, ML model development, deployment, and monitoring. Implement and refine MLOps processes, ensuring robust and scalable delivery of models into production. Plan, initiate, manage, and monitor technical projects from end-to-end. Work with the Product … delivering B2B enterprise cloud applications hosted on AWS. Extensive experience of working with Agile processes, scrum practice and software engineering practices. Solid experience implementing MLOps processes, pipelines, and understanding key ML concepts. Experience building, scaling, and mentoring high-performance teams; adept at aligning teams towards strategic goals. Track record of More ❯

Senior MLops (Full Stack) Engineer | London | Foundation Models What you’ll do Build and maintain APIs (FastAPI or similar) to serve ML models Design and manage robust ML infrastructure using Kubernetes, Docker, and Terraform Deploy machine learning models into production and optimize them for performance Collaborate with ML teams to More ❯

Senior MLops (Full Stack) Engineer | London | Foundation Models What you’ll do Build and maintain APIs (FastAPI or similar) to serve ML models Design and manage robust ML infrastructure using Kubernetes, Docker, and Terraform Deploy machine learning models into production and optimize them for performance Collaborate with ML teams to More ❯

Senior MLops (Full Stack) Engineer London Foundation Models Job details Posted 30 April 2025 Salary £80,000 - £110,000 per annum Benefits: Equity Location: London Job type: Permanent Discipline: AI/Machine Learning Reference: BK-45-1 What you'll do Build and maintain APIs (e.g., FastAPI) to serve ML More ❯

Senior Analyst - Data Science Analyst - Data Science Infosys is seeking a Data Science Analyst with machine learning and Python experience. The ideal candidate will work on productionizing machine learning models and guide the development team for implementing end-to-end More ❯

We're seeking an AI/Machine Learning Engineer to help shape and drive our AI strategy within a newly formed Digital AI Innovation Team. You'll lead the development of AI solutions, build early-stage projects, and establish best More ❯

behaviour and marketing campaign data. Build marketing models such as churn, CLV etc.. Build and deploy various ML models Stay up to date with MLOps and Software best practices. REQUIREMENTS: 4+ Years in proven end to end ML development Specifically within the context of customer behaviour and marketing. Strong communication More ❯

about data and its ability to empower and improve lives. Work with cross-functional teams to deliver production level ML/AI solutions. Implement MLOps with a focus on versioning and data security. Champion Machine Learning across the business. Mentor junior members of the team. Profit share bonus. Skills and More ❯

scalability in reporting and analytics. Partner with Engineering on the design, implementation, and scaling of TrustedHousesitters' data platform, including data lakes, warehouses, pipelines and MLOps systems. Translate complex data into actionable strategies that drive revenue and efficiency. Partner with product, marketing, and finance teams to embed a data-driven culture More ❯

model pipeline engineering, thrives in a collaborative cross-functional team, and wants to grow while gaining exposure to innovative tooling in the LLM and MLOps space Main Purpose of Role LLM/NLP Production Engineering Build and maintain scalable, production-ready pipelines for Natural Language Processing and Large Language Model … ML models and prompt-based LLM workflows using containerised services. Ensure reliable model integration across real-time APIs and batch processing systems. Pipeline Automation & MLOps Use Apache Airflow (or similar) to orchestrate ETL and ML workflows. Leverage MLflow or other MLOps tools to manage model lifecycle tracking, reproducibility, and deployment. … work from home, in the office or remotely. Who is best suited to this role? 2-3 years of experience in ML engineering or MLOps/LLMOps. Strong Python programming skills for data manipulation and pipeline development. Hands-on experience with containerisation using Docker and Kubernetes. Proven experience deploying ML More ❯

Job Title: Product Leader - Global MLOps Platform Location: London Company: Choreograph, a WPP Company WHO WE ARE Choreograph is WPP's global data products and technology company. We're on a mission to transform marketing by building the fastest, most connected data platform that bridges marketing strategy to scaled activation. … WHO WE ARE LOOKING FOR Reporting to the SVP Product, Advanced Analytics, this role will be responsible for setting up and managing our global MLOps platform. This platform will serve as the backbone for all Analytics/AI/ML initiatives across internal teams and clients, ensuring seamless deployment, scalability … have a proven track record in building and/or leading AI/ML platform products and/or in setting up and scaling MLOps platforms within global organizations. The role will also be crucial in setting up and managing the relationship with key internal technical, analytical and data stakeholders More ❯

AI applications using Streamlit . Knowledge Graphs & Semantic Technologies: Work with Neo4j, RDF, or OWL for knowledge representation and data modeling. CI/CD & MLOps: Implement CI/CD pipelines to automate model training, testing, and deployment. Collaboration & Best Practices: Work closely with cross-functional teams to integrate AI solutions … Proficiency in Streamlit for building interactive AI applications. Knowledge of Neo4j, RDF, OWL , and semantic data technologies. Experience with CI/CD pipelines and MLOps for AI model deployment. Strong problem-solving and analytical skills with a focus on scalable AI solutions. More ❯

AI applications using Streamlit . Knowledge Graphs & Semantic Technologies: Work with Neo4j, RDF, or OWL for knowledge representation and data modeling. CI/CD & MLOps: Implement CI/CD pipelines to automate model training, testing, and deployment. Collaboration & Best Practices: Work closely with cross-functional teams to integrate AI solutions … Proficiency in Streamlit for building interactive AI applications. Knowledge of Neo4j, RDF, OWL , and semantic data technologies. Experience with CI/CD pipelines and MLOps for AI model deployment. Strong problem-solving and analytical skills with a focus on scalable AI solutions. More ❯

include analyzing client requirements, managing the ML lifecycle from data collection and model design to deployment and monitoring, and collaborating with data scientists and MLOps engineers to implement models into production. Data Reply offers extensive training and a clear learning path, with opportunities to participate in hackathons, code challenges, and … pipelines for training and deploying models. Implement solutions to monitor model performance in production. Work with cross-disciplinary teams including Data Engineers, Data Scientists, MLOps Engineers, and Data Visualization Specialists. Engage with domain experts to understand and address complex problems. Analyze and communicate client data insights to stakeholders. About the More ❯

and behavioural intelligence models. Lead the transition of prototypes into scalable, cloud-native production systems. Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps). Work with large-scale time series and behavioural data from diverse sensors. Contribute to strategic technical decisions and mentor junior engineers. Collaborate cross-functionally … as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. A background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data More ❯

maintain production-grade Machine Learning systems. You're willing to champion best practices in code quality, testing, observability and MLOps. You have experience with MLOps tools and practices (CI/CD, Docker, Kubernetes) and cloud platforms (GCP, AWS, or Azure). You're a smart, intense, and focussed individual willing … OCR). Optimise AI models and associated systems for performance, scalability, and cost-effectiveness in a production environment. Implement and manage the infrastructure for MLOps, including fine-tuning, deployment, monitoring and versioning. Develop robust data pipelines for ingestion, cleaning, model training, and continuous deployment. Build retrieval-aware repositories for model More ❯

maintain production-grade Machine Learning systems. You're willing to champion best practices in code quality, testing, observability and MLOps. You have experience with MLOps tools and practices (CI/CD, Docker, Kubernetes) and cloud platforms (GCP, AWS, or Azure). You're a smart, intense, and focussed individual willing … OCR). Optimise AI models and associated systems for performance, scalability, and cost-effectiveness in a production environment. Implement and manage the infrastructure for MLOps, including fine-tuning, deployment, monitoring and versioning. Develop robust data pipelines for ingestion, cleaning, model training, and continuous deployment. Build retrieval-aware repositories for model More ❯

A world class Tech Organisation are looking for a Senior Data Scientist (MLOps) to join their division in London on a hybrid basis - opportunity to join a really innovative environment where you'll work with cutting edge technologies. The company: The organisation have been running very successfully now for over … effective use of tools like feature stores and model registries. This role acts as the glue between data science and platform engineering teams, fostering MLOps best practices, addressing bottlenecks in inference and retraining pipelines, and resolving production issues to enhance system robustness and cost efficiency. Key skills and experience: ** Prior More ❯