1 to 25 of 74 Remote 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 ❯

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 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 ❯

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 ❯

design, build, and operationalise production-grade AI systems that directly impact high-stakes projects in the UK. What you'll be doing Designing, building, and deploying software, infrastructure, and MLOps systems that leverage machine learning. Working in cross-functional teams with engineers, data scientists, product managers, and designers. Developing scalable, reusable tools that accelerate ML delivery. Providing technical expertise to More ❯

clear, accessible way Care about documentation, reproducibility, and teaching others "the why" behind decisions Nice To Have Exposure to telematics or usage-based insurance data Experience designing or maintaining MLOps platforms Hands-on experience with insurance pricing tools like Akur8, Emblem or similar pricing modelling tools What's it like to work at Zego? Joining Zego is a career-defining More ❯

must be current) Strong experience in AI/ML engineering (Python, TensorFlow, PyTorch, etc.) Experience with cloud platforms (AWS, Azure, or GCP) Solid understanding of data pipelines, APIs, and MLOps Excellent problem-solving and communication skills More ❯

self-motivated drive to take ownership of tasks Tech Stack Core : Python, FastAPI, asyncio, Airflow, Luigi, PySpark, Docker, LangGraph Data Stores : Vector Databases, DynamoDB, AWS S3, AWS RDS Cloud & MLOps : AWS, Databricks, Ray ️ Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year Fully remote team - choose where you live ️ Work from home More ❯

spaces). Lead architectural discussions and technical trade-offs while staying close enough to dive into details when needed. Know your way around cloud infrastructure (AWS preferred) and modern MLOps practices. Thrive in a collaborative, startup-style environment: adaptable, decisive, and excited to work cross-functionally to deliver real business impact. Benefits We're a scaling start up, and we More ❯

Proven mentoring and coaching experience. Ability to drive continuous improvement and champion change within project contexts. An interest in applying DevOps principles in Data & AI environments is beneficial (e.g. MLOps, data ops) Recruitment process The recruitment process you can expect for this role is an initial call with your dedicated Talent Acquisition Partner who will chat with you about Waracle More ❯

ready AI/ML solutions in financial services; specific project examples required. Proficiency in designing and implementing scalable, secure AI solutions, including data pipelines, model deployment, API integration, and MLOps best practices such as Trustworthy AI. Education and Experience: Bachelor's degree or equivalent in Computer Science, Data Science, Engineering, or a related field, Master's or PhD (or equivalent More ❯

Learning) You're confident in Python (production-level) and SQL, and at home with modern ML libraries such as Pandas, scikit-learn, and TensorFlow You have practical experience with MLOps frameworks and deploying models You're skilled at bringing data to life through visualisation, and tools like Tableau feel natural to you You're comfortable working with cloud-based architectures More ❯

and pre-sales activities Maintain high billable utilisation while delivering exceptional client value Contribute to Made Tech's thought leadership in AI/ML Guide clients in building robust MLOps practices and data-driven cultures Hiring and line-managing data scientists and analysts Experience in the following things isn't essential, but it's highly desirable Central Digital & Data Office More ❯

we’re looking for: Proven experience in AI/ML model development and deployment Strong skills with Python, TensorFlow/PyTorch, and cloud platforms (AWS/Azure/GCP) MLOps assurance and risk experinece Knowledge of data pipelines, model optimisation, and real-world deployments Details: Contract: 6 months (with view to extend) Location: London (Hybrid) Start: ASAP If you’re More ❯