101 to 125 of 404 MLOps Jobs in the UK

and ownership Nice to Have Experience with Data Mesh or Data Lake architectures Familiarity with Kubernetes , Docker, and real-time streaming (Kafka, Kinesis) Exposure to ML engineering pipelines or MLOps Interested? If you're ready to lead a team at the forefront of data innovation in a mission-driven scale-up, apply today or reach out for a confidential chat. More ❯

of complex business cloud solutions. The ideal candidate will have a strong background in Machine Learning engineering and an expert in operationalising models in the Databricks MLFlow environment (chosen MLOps Platform). Responsibilities: Collaborate with Data Scientists and operationalize the model with auditing enabled, ensure the run can be reproduced if needed. Implement Databricks best practices in building and maintaining More ❯

to solve client challenges Collaborate with client stakeholders to understand business requirements and shape technical approaches Contribute to the delivery of scalable, production-ready solutions alongside data engineers and MLOps teams Apply a range of techniques including LLMs, RAG pipelines, vector databases, prompt engineering, and fine-tuning Participate in client workshops and discovery sessions to gather requirements and present findings More ❯

in NLP, unstructured data, and information extraction Eagerness to learn, take feedback, and contribute to a collaborative team Nice to Have: Experience with SQL/NoSQL databases Familiarity with MLOps tools (Docker, Git, CI/CD) Exposure to vector databases or semantic search Knowledge of financial datasets or document processing workflows If youre excited to grow your skills in machine More ❯

CI/CD pipelines. Experience writing clean, efficient, and modular code suitable for production environments. Desirable Skills or Knowledge Familiarity with AMO physics or quantum machine learning. Experience with MLOps best practices. Knowledge of systems like Apache Kafka, MQTT or real-time data pipelines. Experience with cloud platforms (AWS, Azure, GCP). Deep expertise in time series modelling techniques (e.g. More ❯

to automation and deployment pipelines to support the efficient execution of BioAI projects. Collaborate with researchers and biologists to translate scientific goals into efficient software solutions. Utilize DevOps/MLOps practices and cloud-based infrastructures to ensure scalability and reliability. Provide clear, well-structured reporting and communication of results and technical designs to internal teams and external collaborators. Requirements A More ❯

Snowflake Schema, Data Vault etc.) Past hands-on development experience in at least one enterprise analytics database like Oracle/Terradata/SQL Server/Snowflake Good understanding of MLOPS Good/In depth experience of Oracle stack - database, oracle analytics, ODI, Golden gate Good knowledge of common big data platforms and best practices Experience of working in an Agile More ❯

Snowflake Schema, Data Vault etc.) Past hands-on development experience in at least one enterprise analytics database like Oracle/Terradata/SQL Server/Snowflake Good understanding of MLOPS Good/In depth experience of Oracle stack - database, oracle analytics, ODI, Golden gate Good knowledge of common big data platforms and best practices Experience of working in an Agile More ❯

supervised and unsupervised learning with an emphasis on vision. Proficiency with deep learning frameworks such as TensorFlow/PyTorch. Proficiency with Python and strong software development background. Experience with MLOps practices, including versioning, deployment, and monitoring of models highly desirable. Ability to communicate complex technical concepts clearly to non-technical stakeholders. Why Work for Proximie? You will be encouraged to More ❯

frameworks (such as Scikit-learn, TensorFlow, PyTorch, Hugging Face) and data manipulation tools (Pandas, NumPy), as well as version control, containerisation, and ML deployment pipelines. Understands how to apply MLOps principles in production environments To be successful in this role you must have hands-on experience designing and deploying ML models in industryideally within agile or cross-functional teams. Understands … to make a difference. Required Knowledge and experience Technical skills: Confident user of MSTeams Strong applied experience in machine learning and/or data science roles Solid understanding of MLOps and production deployment practices Experience with Python and core ML libraries (e.g., Scikit-learn, Pandas, PyTorch, TensorFlow) Familiarity with cloud platforms and data infrastructure (e.g., AWS/GCP/Azure More ❯

client-facing 🎯 Must-haves: 8+ years in Data Science/ML Engineering 2+ years hands-on with Databricks Strong track record delivering production-grade ML models Solid grasp of MLOps best practices Confident speaking to technical and non-technical stakeholders 🛠️ Tech you’ll be using: Python, SQL, Spark, R MLflow, vector databases GitHub/GitLab/Azure DevOps Jira, Confluence More ❯

client-facing 🎯 Must-haves: 8+ years in Data Science/ML Engineering 2+ years hands-on with Databricks Strong track record delivering production-grade ML models Solid grasp of MLOps best practices Confident speaking to technical and non-technical stakeholders 🛠️ Tech you’ll be using: Python, SQL, Spark, R MLflow, vector databases GitHub/GitLab/Azure DevOps Jira, Confluence More ❯

research and apply new tools, techniques, and technologies. Experience with: Cloud deployment,Neural networks and libraries like TensorFlow, XGBoost, CatBoost, SKlearn, API development, SQL,CI/CD, DevOps, or MLOps pipelines Experience with: Strong hands-on experience or genuine interest in data science and analytics. Proficiency in Python and familiarity with testing frameworks (e.g., pytest). Ability to work both More ❯

research and apply new tools, techniques, and technologies. Experience with: Cloud deployment,Neural networks and libraries like TensorFlow, XGBoost, CatBoost, SKlearn, API development, SQL,CI/CD, DevOps, or MLOps pipelines Experience with: Strong hands-on experience or genuine interest in data science and analytics. Proficiency in Python and familiarity with testing frameworks (e.g., pytest). Ability to work both More ❯

a talented team of researchers to improve and refine algorithms for real-world tasks Ensure the scalability and maintainability of production systems, with a strong focus on (low-level) MLOps What You’ll Be Doing (Machine Learning Researcher): Conduct groundbreaking research to develop new algorithms and models for robotics Work on advanced learning approaches such as reinforcement learning and imitation More ❯

a talented team of researchers to improve and refine algorithms for real-world tasks Ensure the scalability and maintainability of production systems, with a strong focus on (low-level) MLOps What You’ll Be Doing (Machine Learning Researcher): Conduct groundbreaking research to develop new algorithms and models for robotics Work on advanced learning approaches such as reinforcement learning and imitation More ❯

a talented team of researchers to improve and refine algorithms for real-world tasks Ensure the scalability and maintainability of production systems, with a strong focus on (low-level) MLOps What You’ll Be Doing (Machine Learning Researcher): Conduct groundbreaking research to develop new algorithms and models for robotics Work on advanced learning approaches such as reinforcement learning and imitation More ❯

a talented team of researchers to improve and refine algorithms for real-world tasks Ensure the scalability and maintainability of production systems, with a strong focus on (low-level) MLOps What You’ll Be Doing (Machine Learning Researcher): Conduct groundbreaking research to develop new algorithms and models for robotics Work on advanced learning approaches such as reinforcement learning and imitation More ❯

a talented team of researchers to improve and refine algorithms for real-world tasks Ensure the scalability and maintainability of production systems, with a strong focus on (low-level) MLOps What You’ll Be Doing (Machine Learning Researcher): Conduct groundbreaking research to develop new algorithms and models for robotics Work on advanced learning approaches such as reinforcement learning and imitation More ❯

desirable) Hands-on expertise in areas such as: Cloud development platforms such as AWS, Microsoft Azure, Google Cloud DevOps & CI/CD such as Jenkins, Docker, Kubernetes AI Development & MLOps A growth mindset and willingness to learn new technologies is essential. What We Offer Access to innovative teaching tools and methods A collaborative, passionate academic community Opportunities for professional development More ❯

pipelines. Comfortable in fast-paced, agile delivery environments. DESIRABLE SKILLS Experience building or integrating feature stores . Familiarity with Unity Catalog , Databricks SQL , and cost optimisation . Exposure to MLOps practices and production-grade model lifecycle management. Prior experience in financial services or other regulated sectors. HOW TO APPLY Please register your interest by sending your CV via the apply More ❯

databases. Experience with containerisation (Docker, Kubernetes/EKS). Knowledge of healthcare data standards such as CDISC, HL7, FHIR, SNOMED CT, OMOP, and DICOM. Familiarity with big data technologies, MLOps, and model deployment. Bachelor's degree in a relevant field (Master's preferred) and 5-7 years' experience in data engineering, including work with healthcare, research, or clinical data. More ❯

Strong communication and stakeholder management skills, with the ability to influence at C-level Background as a hands-on data scientist, with deep understanding of model development, deployment, and MLOps MSc in a quantitative field required; PhD welcome but not essential Familiarity with AI governance and ethical AI practices Curious and up to date on GenAI technologies (either directly or More ❯

scalable AI solutions using cutting-edge tools like LangGraph, FastAPI, and HuggingFace. Own the full AI product lifecycle - from idea to production. Architect intelligent systems using Python, microservices, and MLOps tooling (MLflow, DVC). Work closely with cross-functional teams to turn real-world problems into working software. 🛠️ What You Bring: Fluency in Python and strong grasp of ML/ More ❯

scalable AI solutions using cutting-edge tools like LangGraph, FastAPI, and HuggingFace. Own the full AI product lifecycle - from idea to production. Architect intelligent systems using Python, microservices, and MLOps tooling (MLflow, DVC). Work closely with cross-functional teams to turn real-world problems into working software. 🛠️ What You Bring: Fluency in Python and strong grasp of ML/ More ❯