1 to 25 of 146 MLOps Jobs in the UK

/GenAI strategies aligned with business objectives. Designing and developing NLP solutions using techniques such as text classification, NER, topic modeling, and text generation. Collaborating with data engineers and MLOps teams to ensure clean data pipelines and seamless model integration. Applying LLMs (e.g., GPT, BERT, LLaMA2) and knowledge graphs to enhance natural language understanding and reasoning. Conducting exploratory data analysis More ❯

scalable AI applications across the enterprise. Work with a multi-functional team (DevOps, data engineers, developers, testers, Infosec) to productionize AI services on AWS. Enhance our tech stack, including MLOps, CI/CD pipelines, UI, and AI Python libraries. Develop prompts, fine-tune models, and track results. Evaluate third-party GenAI and LLM technologies for cost-benefit analysis. Deliver projects More ❯

skills and ability to present complex ideas to non-technical stakeholders Experience with cloud platforms (AWS, GCP, Azure) and tools like Databricks, Snowflake, or BigQuery Desirable Skills Familiarity with MLOps, model monitoring, and production deployment Experience in a specific domain (e.g., marketing, operations, fraud, personalization, NLP) is a plus Hands-on experience with LLM stacks (e.g., Mistral, LangChain, Chroma, Hugging More ❯

and associated regulatory requirements. Exposure to healthcare data standards (CDISC, HL7, FHIR, SNOMED CT, OMOP, DICOM). Experience to big data technologies and handling. Knowledge of machine learning operations (MLOps) and model deployment. Strong problem-solving and analytical abilities. Excellent communication skills for collaborating with stakeholders. Experience working in an Agile development environment. Required/Preferred Education Bachelor’s Degree More ❯

Engineering, Data Science, or related field. Experience with streaming data technologies (e.g., Kafka, Kinesis). Familiarity with data cataloging and metadata management tools. Exposure to machine learning pipelines or MLOps is a bonus. At bp, we provide the following environment and benefits to you: A company culture where we respect our diverse and unified teams, where we are proud of More ❯

Engineering, Data Science, or related field. Experience with streaming data technologies (e.g., Kafka, Kinesis). Familiarity with data cataloging and metadata management tools. Exposure to machine learning pipelines or MLOps is a bonus. At bp, we provide the following environment and benefits to you: A company culture where we respect our diverse and unified teams, where we are proud of More ❯

Engineering, Data Science, or related field. Experience with streaming data technologies (e.g., Kafka, Kinesis). Familiarity with data cataloging and metadata management tools. Exposure to machine learning pipelines or MLOps is a bonus. At bp, we provide the following environment and benefits to you: A company culture where we respect our diverse and unified teams, where we are proud of More ❯

and optimize LLMs for quality, latency, sustainability and cost-effective performance. Programming and NLP Tooling: Advanced Python proficiency and expertise with frameworks like PyTorch, TensorFlow, Hugging Face, or LangChain. MLOps and Deployment: Experience with containerization tools (Docker, Kubernetes) and workflow management tools (Azure ML Studio, MLFlow). Cloud and AI Infrastructure: Hands-on experience with (preferably Azure) Cloud environments for More ❯

and explain technical concepts in non-technical terms. Demonstrable experience mentoring junior team members and fostering collaboration within teams. Desirable Experience: Basic familiarity with CI/CD pipelines and MLOps practices, including automated testing, model versioning, and monitoring workflows.Hands-on experience with containerisation and orchestration technologies (e.g., Docker, Kubernetes) to support AI/ML model deployment.Proficiency in cleansing, filtering, and More ❯

and associated regulatory requirements. Exposure to healthcare data standards (CDISC, HL7, FHIR, SNOMED CT, OMOP, DICOM). Exposure to big data technologies and handling. Knowledge of machine learning operations (MLOps) and model deployment. Strong problem-solving and analytical abilities. Excellent communication skills for collaborating with stakeholders. Experience working in an Agile development environment. Required/Preferred Education Bachelor’s Degree More ❯

programming, software design, i.e., SOLID principles, and testing practices. Knowledge and working experience of AGILE methodologies. Proficient with SQL. Familiarity with Databricks, Spark, geospatial data/modelling Exposure to MLOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc. are a plus. Additional Information What’s in it for you?: Competitive salary that reflects More ❯

real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data tools (Spark, etc.). Strong written and verbal communication skills, especially More ❯

model endpoints, pipelines, embeddings, vector search) or equivalent cloud-native ML platforms (e.g. AWS SageMaker, Azure ML) and agent orchestration frameworks such as LangChain and LangGraph Solid understanding of MLOps - CI/CD, IaC (Terraform), experiment tracking, model registry, and monitoring. Proven experience deploying and operating ML systems in production (batch and real-time). Familiarity with RAG architectures, prompt More ❯

class developer experience to accelerate customer success. Deployment & Integration: Master and advise on modern cloud deployment patterns using containers (e.g., Docker) and cloud images. Help customers integrate with their MLOps pipelines and data workflows. Voice of the Customer: Act as the primary technical point of contact for our users. Systematically gather customer feedback, identify pain points, and translate them into More ❯

Deep technical proficiency with LLMs, NLP, Python, SQL, and major AI/ML frameworks (e.g., PyTorch, TensorFlow). Strong understanding of AI engineering fundamentals including DevOps, CI/CD, MLOps, and DevSecOps. Experience building AI governance frameworks to address ethical risk, model accuracy, and regulatory compliance. Why Join? This is a career-defining opportunity to shape the AI strategy of More ❯

redefining how advanced AI is deployed across Defence. What You'll Do Lead the design and deployment of machine learning infrastructure and software for Defence programmes. Build scalable, reusable MLOps tools to accelerate project delivery. Work closely with data scientists, engineers, and product teams to integrate advanced AI into mission-critical systems. Engage directly with clients to understand technical requirements More ❯

redefining how advanced AI is deployed across Defence. What You'll Do Lead the design and deployment of machine learning infrastructure and software for Defence programmes. Build scalable, reusable MLOps tools to accelerate project delivery. Work closely with data scientists, engineers, and product teams to integrate advanced AI into mission-critical systems. Engage directly with clients to understand technical requirements More ❯

build, and deploy production-grade ML systems that have a direct impact on government services and policy delivery. What you'll be doing Designing and delivering software, infrastructure, and MLOps systems that bring ML models into real-world use. Collaborating in cross-functional teams with engineers, data scientists, product managers, and designers. Creating scalable, reusable tools that improve ML deployment More ❯

practicing the importance of Secure Software Development. Having skills in technologies such as Kubernetes, Docker and Database engineering (PostgreSQL/DynamoDB) would be desirable but not essential. Exposure to MLOps practices for deploying and monitoring AI models in production would also be highly desirable. Role at a glance: Senior Software Engineer (AI) Fully remote or Hybrid positions available (UK only More ❯

practicing the importance of Secure Software Development. Having skills in technologies such as Kubernetes, Docker and Database engineering (PostgreSQL/DynamoDB) would be desirable but not essential. Exposure to MLOps practices for deploying and monitoring AI models in production would also be highly desirable. Role at a glance: Senior Software Engineer (AI) Fully remote or Hybrid positions available (UK only More ❯

/infrastructure, with at least 5 years leading large teams. Deep expertise in distributed systems, model training infrastructure, and inference platforms. Strong experience with cloud platforms (AWS, GCP, Azure), MLOps/DevOps, and security. Excellent leadership, communication, and stakeholder management skills. Preferred Advanced technical degree (MS/PhD). Strong knowledge of data systems (SQL/NoSQL, Spark, Kafka, Flink More ❯

methods? Any experience of popular known deployment methods on k8s cluster? Gitops/Git/Jenkins Any experience using gitops pipeline? Nice to have Understanding of LLM Evaluation Frameworks MLOps platforms or LLMOps background Understanding of AI Robert Walters Operations Limited is an employment business and employment agency and welcomes applications from all candidates More ❯

and transformer-based architectures. Strong Python skills and familiarity with key ML/DL libraries. Experience with Azure (or similar cloud platforms), containerization (Docker/Kubernetes a plus), and MLOps tools. Understanding of healthcare data privacy, compliance (e.g., ISO standards), and secure data handling. Strong communication skills and ability to work cross-functionally in a collaborative environment McGregor Boyall is More ❯

engineering. Experience in a recent technical lead or architect-level role. Proven delivery of large-scale data systems using cloud platforms (AWS, Azure, or GCP). Deep knowledge of MLOps practices (MLflow, Docker, Kubernetes, etc.). Demonstrated experience in building Data-as-a-Service (DaaS) solutions or data APIs. Strong stakeholder engagement and mentoring skills. Desirable: Experience in insurance, financial More ❯

and transformer-based architectures. Strong Python skills and familiarity with key ML/DL libraries. Experience with Azure (or similar cloud platforms), containerization (Docker/Kubernetes a plus), and MLOps tools. Understanding of healthcare data privacy, compliance (e.g., ISO standards), and secure data handling. Strong communication skills and ability to work cross-functionally in a collaborative environment McGregor Boyall is More ❯