18 of 18 MLflow Jobs in the UK excluding London

learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using PySpark. Solid understanding of software engineering principles and version control (e.g., Git). Excellent ...

Infrastructure as Code (Terraform), Docker - containerisation. An understanding of kubernetes. Understanding of LLM architectures, inference serving optimization techniques (quantisation, caching), and MLOps tooling (e.g., MLFlow, Kubeflow). Proven experience designing, implementing, and optimising complex RAG pipelines using vector databases (e.g., Pinecone, PGVector). Practical experience with agentic frameworks (e.g., LangChain ...

practices, version control (Git), or CI/CD pipelines Understanding of deep learning, NLP, or computer vision Familiarity with deployment tools like Docker or MLflow What You’ll Gain Hands-on Experience : Work on real ML systems and contribute to production-grade solutions Mentorship & Training : Learn from senior ML engineers ...

working with large datasets and data pipelines Desirable Experience Experience with Generative AI or large language models Exposure to tools such as Hugging Face, MLflow, Kubeflow, or similar Knowledge of NLP, computer vision, or recommendation systems Experience working in agile or product-led environments Whats on Offer Competitive salary ...

embeddings, vector search, and Generative AI architectures. Practical experience using Hugging Face, OpenAI, LangChain, Retrieval Augmented Generation, and diffusion models. Strong MLOps experience including MLflow, Kubeflow, Airflow, Docker, Kubernetes, and CI and CD tooling. Strong programming skills in Python. Bash, SQL, and JavaScript are desirable. Proven experience working with large ...

frameworks such as PyTorch (preferred), TensorFlow, or Scikit-learn? Experience with NLP, deep learning, or computer vision? Familiarity with MLOps tools (Azure ML Pipelines, MLflow, Docker, Kubernetes)? Experience working with cloud platforms such as Azure, GCP, or AWS? The abbility to engage with technical and non-technical teams? Would ...

role in shaping product direction and driving large-scale business impact. Tech Stack Cloud ML platforms, Python, Spark, SQL, CI/CD pipelines, MLflow, TensorFlow, PyTorch, Scikit-learn. What You’ll Do Build high-impact AI/ML systems that deliver clear business outcomes. Leverage hands-on experience with modern ...

process. Strong knowledge of big data tool such as Spark, Databricks and Python. Strong understanding of common machine learning techniques and frameworks (e.g. mlflow). Strong knowledge of Natural language processing (NPL) concepts. Strong knowledge of scrum practices and agile mindset. Skills & Core competences Strong Analytical and Problem-Solving Skills ...

deploying cutting-edge machine learning solutions across the company.If you enjoy end-to-end ownership (from experimentation to deployment), working with AWS, Docker, MLflow, TensorFlow/PyTorch, and contributing to innovative projects with a flexible, results-focused culture, this could be an exciting match. Skills: Ability to write and produce ...

Strong design and development skills using Python. Python's libraries for machine learning: PySpark, Pytorch, scikit-learn and pandas. Technical experience using Databricks and MLFlow (Other Platforms can be considered). Good understanding of software code review standards - CI/CD. Stochastic Simulation modelling experience. If you are interested ...

industry experience. Essential Skills Excellent knowledge and experience of managing an on-premise Kubernetes 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 ...

industry experience. Essential Skills Excellent knowledge and experience of managing an on-premise Kubernetes 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 ...

library skills Hands-on experience with GenAI APIs and production deployments Knowledge of the full ML lifecycle and MLOps tools such as MLflow or SageMaker Strong communication skills and experience working with senior stakeholders A grounding in statistics and an agile, problem solving mindset Some Scala exposure is a bonus ...

Machine Learning Engineer Machine Learning Engineer - AI for Advanced Materials - Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join … Machine Learning Engineers with experience in some or all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join ...

LangChain, LangGraph, or custom). Create and maintain data pipelines (Airflow, dbt, Step Functions). Implement monitoring, observability, and automated retraining (CloudWatch, Prometheus, Grafana, MLflow). Embed strong security, compliance, and guardrail practices across all ML workflows. Mentor junior engineers and promote engineering best practices. Key Requirements Essential 3+ years … SageMaker, EKS/Fargate, Lambda, Step Functions, S3). Proficient with Docker, Kubernetes , and IaC (Terraform or AWS CDK). Experience with MLflow , CI/CD tools, and automated testing. Hands-on with LLM deployment and multi-agent systems . Proven experience building data pipelines and production ML workflows. Strong ...

business requirements into technical solutions. Optimize and deploy models using tools like TensorFlow Serving, TorchServe, ONNX, and TensorRT. Build and manage ML pipelines using MLflow, Kubeflow, and Azure ML Pipelines. Work with large-scale data using PySpark and integrate models into production environments. Monitor model performance and retrain as needed … learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using PySpark. Solid understanding of software engineering principles and version control (e.g., Git). Excellent ...

base salary Hybrid working with three days in the London office Work with advanced AI platforms including Azure ML, Azure OpenAI, Databricks, MLflow and LangChain Global exposure and the opportunity to work with senior stakeholders across time zones A collaborative, supportive culture that encourages innovation and professional development What … environments Strong knowledge of Python, ML frameworks (PyTorch, TensorFlow), and cloud platforms (Azure preferred) Experience operationalising models using tools such as Azure ML, Databricks, MLflow Understanding of data engineering, data governance, and lakehouse architectures Excellent communication skills with the ability to simplify complex concepts for non-technical stakeholders A proactive ...

will: Build robust ML and MLOps pipelines for scalable, reproducible model development, deployment, and monitoring. Use tools such as Airflow for workflow orchestration and MLflow for experiment tracking, model registry, and lifecycle management. Work within an agile development environment and help prioritise high-value opportunities for rapid delivery. Essential Skills … skills Hands-on experience developing ML and/or deep learning models for scientific or engineering problems Experience with MLOps tools such as Airflow, MLflow, and containerisation (e.g., Docker) Strong data-visualisation and storytelling skills Interest in materials discovery, computer vision, big data, or optimisation Collaborative communicator, organised, proactive ...