15 of 15 MLflow Jobs in the South East

or Azure) Ability to work independently and communicate effectively in a remote team Bonus Points Experience with Hugging Face Transformers , LangChain , or RAG pipelines Knowledge of MLOps tools (e.g. MLflow, Weights & Biases, Docker, Kubernetes) Exposure to data engineering or DevOps practices Contributions to open-source AI projects or research publications What We Offer Fully remote working A collaborative and inclusive More ❯

foundational LLMs to custom built cognitive agents, solving real world business challenges. Establishing scalable ML/AI pipelines and infrastructure, working closely with data engineering and DevOps functions (Kubernetes, MLflow, Vertex AI, etc.). Acting as a thought leader, identifying new AI use cases and communicating technical vision to executive stakeholders and cross-functional teams. Champion ethical AI principles, ensuring More ❯

learn, TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker, Vertex AI) Comfortable working independently and delivering high-quality work to tight timelines Experience working in fast-paced environments or scale-up settings Company Market leading financial services (fintech More ❯

relevant academic (research Masters level) and/or industry experience. Excellent knowledge and experience of managing an on-premise Kubenetes cluster. Excellent knowledge of Kubeflow and similar systems, e.g. MLflow Good programming ability in Python with familiarity with Linux systems including scripting and system configuration. Experience using AWS, e.g, Cognito, S3, EC2, Lamdas, etc. Experience with ML toolkits, e.g. PyTorch More ❯

including APIs, data structures, and async processing* Databricks/Microsoft Fabric* Cloud, preferably Azure (Data Lake, Functions, App Services)* Containerisation with Docker and CI/CD pipelines* MLOps tooling (MLFlow, Git-based versioning, environment tracking)Desirable Skills & Interests* LangChain, Langflow, or similar frameworks for building AI agents* LLMs or intelligent automation workflows* High-availability, scalable systems (microservices, event-based architectures More ❯

background in data engineering, analytics, or data science. Experience with modern data stacks (e.g., SQL, dbt, Airflow, Snowflake, Looker/Power BI) and AI/ML tooling (e.g., Python, MLflow, MLOps). A track record of building and managing high-performing data teams. Strategic thinking and ability to influence senior stakeholders, comfortable in dual-regulated environments. HOW TO APPLY: Please More ❯

Experience Academic background (research Masters level) or industry experience in a relevant field Strong experience managing on premise Kubernetes clusters Deep knowledge of Kubeflow or similar systems such as MLflow Proficient in Python and experienced with Linux systems Familiar with AWS services such as Cognito, S3, EC2 and Lambda Experience working with ML frameworks such as PyTorch or Lightning Capable More ❯

Experience Academic background (research Masters level) or industry experience in a relevant field Strong experience managing on premise Kubernetes clusters Deep knowledge of Kubeflow or similar systems such as MLflow Proficient in Python and experienced with Linux systems Familiar with AWS services such as Cognito, S3, EC2 and Lambda Experience working with ML frameworks such as PyTorch or Lightning Capable More ❯

call expectation outside of core office hours . Key Responsibilities: Manage and maintain on-premise Kubernetes clusters Implement and maintain ML Ops pipelines using Kubeflow and similar tools (e.g., MLflow) Develop scripts and tooling in Python; manage Linux system configurations Leverage AWS infrastructure (Cognito, S3, EC2, Lambda, etc.) Integrate ML toolkits (e.g., PyTorch, Lightning) into ML Ops workflows Design and More ❯

research Masters level) and/or industry experience. Essential Skills Excellent knowledge and experience of managing an on-premise Kubenetes cluster. Excellent knowledge of Kubeflow and similar systems, e.g. MLflow Good programming ability in Python with familiarity with Linux systems including scripting and system configuration. Experience using AWS, e.g, Cognito, S3, EC2, Lamdas, etc. Experience with ML toolkits, e.g. PyTorch More ❯

call expectation outside of core office hours . Key Responsibilities: Manage and maintain on-premise Kubernetes clusters Implement and maintain ML Ops pipelines using Kubeflow and similar tools (e.g., MLflow) Develop scripts and tooling in Python; manage Linux system configurations Leverage AWS infrastructure (Cognito, S3, EC2, Lambda, etc.) Integrate ML toolkits (e.g., PyTorch, Lightning) into ML Ops workflows Design and More ❯

native environments Strong technical background in data engineering, analytics, or science Experience working with Finance and Risk teams Familiar with AWS and modern data/AI stacks (SQL, Python, MLflow, MLOps) Strategic mindset with ability to scale teams and influence at C-level More ❯

/CD pipelines, unit testing, use of version control systems. Dashboarding and Data Visualization Skills (e.g. Streamlit, Dash, Retool, Plotly) Exposure to ML libraries/systems (Scikit-learn, PyTorch, MLflow) Clinical trials Good Clinical Practice (GCP) Medical device development About Us All our benefits information can be found in the downloadable Benefits document under 'Information' on the right hand side More ❯

research Masters level) and/or industry experience. Essential Skills Excellent knowledge and experience of managing an on-premise Kubenetes cluster. Excellent knowledge of Kubeflow and similar systems, e.g. MLflow Good programming ability in Python with familiarity with Linux systems including scripting and system configuration. Experience using AWS, e.g, Cognito, S3, EC2, Lamdas, etc. Experience with ML toolkits, e.g. PyTorch More ❯

Cloud services (Data Lake, Functions, App Services) for development and deployment Implement and maintain containerized solutions using Docker and CI/CD pipelines Apply MLOps practices using tools like MLFlow , Git-based versioning, and environment tracking Build and integrate AI and intelligent automation frameworks Ensure applications meet performance, reliability, and scalability requirements Required Skills & Experience: 2+ years of Python development … Proficiency in Azure cloud services including Data Lake, Functions, and App Services Strong understanding of Docker , CI/CD workflows, and automation pipelines Familiarity with MLOps tooling such as MLFlow, Git version control, and environment management Desirable Skills & Interests: Experience with frameworks like LangChain , Langflow , or similar tools for building AI agents Understanding of Large Language Models (LLMs) and intelligent More ❯