1 to 25 of 39 Permanent MLflow Jobs in the UK excluding London

modern ML frameworks (e.g., PyTorch, TensorFlow, JAX). Strong command of cloud-native AI tooling (e.g., AWS SageMaker, GCP Vertex AI, AzureML/AzureAI, MLflow, Weights & Biases). Well-rounded Engineer : Comfortable working with version-controlled codebases, DevOps pipelines, containerisation/microservices (Docker/Kubernetes), and Infrastructure-as-Code (Terraform More ❯

in production cloud environments. Advanced Python: Expertise in developing efficient, production-grade AI/ML code. LLMOps & AI Model Management: Experience with tools like MLFlow, LangChain, Hugging Face, Kubeflow, or similar platforms. Data Processing: Proficient with Databricks/Spark for large-scale AI data processing. SQL: Strong capabilities in data More ❯

in production cloud environments. Advanced Python: Expertise in developing efficient, production-grade AI/ML code. LLMOps & AI Model Management: Experience with tools like MLFlow, LangChain, Hugging Face, Kubeflow, or similar platforms. Data Processing: Proficient with Databricks/Spark for large-scale AI data processing. SQL: Strong capabilities in data More ❯

and data modeling. Familiarity with cloud platforms (AWS, Azure, GCP) for deploying ML and data solutions. Knowledge of MLOps practices and tools, such as MLflow or Kubeflow. Strong problem-solving skills, with the ability to troubleshoot both ML models and data systems. A collaborative mindset and ability to work in More ❯

Environment: Python, PyTorch or TensorFlow AWS (including SageMaker, S3, Lambda) or Azure ML Docker, Kubernetes, Airflow CI/CD tools (e.g. GitHub Actions, Jenkins) MLflow or similar frameworks Required Experience: Proven track record of deploying machine learning models to production Strong programming skills in Python and familiarity with modern ML More ❯

NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations or regulated industries. More ❯

Desirable Experience of Microsoft Fabric Experience of Microsoft Dynamics Experience with data governance and compliance frameworks Proficiency in AI/ML frameworks (TensorFlow, PyTorch, MLflow) Knowledge of Agile and DevOps methodologies Other Stuff Benefits include 25 Days Annual Leave, Medical Insurance, Flexible Hybrid/Home Working, 5% Employer Contribution Pension More ❯

teams. Familiarity with LLM (Large Language Model) pipelines and vector databases (e.g. Pinecone, FAISS). Background in data versioning and experiment tracking (e.g DVC, MLflow). Familiarity with time-series datasets and databases. Why Join Quantum? Work at the forefront of AI innovation with a team passionate about changing the More ❯

proficiency in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or email me at mmatysik@trg-uk.com. More ❯

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 🎓 Bonus points for: MSc/PhD in ML or AI Databricks ML Engineer (Professional) certified More ❯

/GCP. · Ability to manage cloud infrastructure to ensure high availability, scalability, and cost efficiency. Nice-to-Have · Experience with ML orchestration platforms like MLflow, SageMaker Pipelines, Kubeflow, or similar. · Familiarity with model quantization, pruning, or other performance optimization techniques. · Exposure to distributed training frameworks like Unsloth, DeepSpeed, Accelerate, or More ❯

. This role is ideal for someone who enjoys blending technical precision with innovation. You’ll: Build and manage ML pipelines in Databricks using MLflow, Delta Lake, Spark, and Mosaic AI. Train and deploy generative models (LLMs, GANs, VAEs) for NLP, content generation, and synthetic data. Architect scalable solutions using More ❯

and machine learning solutions. Key Responsibilities Engineer and maintain modern data platforms with a strong focus on Databricks, including Delta Lake, Apache Spark, and MLflow Build and optimise CI/CD pipelines, infrastructure-as-code (IaC), and cloud integrations (Azure preferred, AWS/GCP beneficial) Collaborate with data engineers, architects More ❯

teams. Deep knowledge of media measurement techniques, such as media mix modelling. Experience with advanced AI techniques, including NLP, GenAI, and CausalAI. Familiarity with MLFlow, API design (FastAPI), and dashboard building (Dash). If this role looks of interest, reach out to Joseph Gregory More ❯

Git, Linux, and command-line tools. Desirable: Experience with medical image processing, DICOM, ITK/SimpleITK. Familiarity with deploying ML models or MLOps tools (MLFlow, Kubernetes, DVC, Docker). Understanding of the software development lifecycle. Clinical research or commercial experience in regulated/healthcare domains. If you're interested in More ❯

Git, Linux, and command-line tools. Desirable: Experience with medical image processing, DICOM, ITK/SimpleITK. Familiarity with deploying ML models or MLOps tools (MLFlow, Kubernetes, DVC, Docker). Understanding of the software development lifecycle. Clinical research or commercial experience in regulated/healthcare domains. If you're interested in More ❯

Git, Linux, and command-line tools. Desirable: Experience with medical image processing, DICOM, ITK/SimpleITK. Familiarity with deploying ML models or MLOps tools (MLFlow, Kubernetes, DVC, Docker). Understanding of the software development lifecycle. Clinical research or commercial experience in regulated/healthcare domains. If you're interested in More ❯

Git, Linux, and command-line tools. Desirable: Experience with medical image processing, DICOM, ITK/SimpleITK. Familiarity with deploying ML models or MLOps tools (MLFlow, Kubernetes, DVC, Docker). Understanding of the software development lifecycle. Clinical research or commercial experience in regulated/healthcare domains. If you're interested in More ❯

years leading Databricks-based solutions. Proven experience in a consulting environment delivering large-scale data platform projects. Hands-on expertise in Spark, Delta Lake, MLflow, Unity Catalog, and DBSQL. Strong proficiency in Python, SQL, and at least one major cloud platform (AWS, Azure, or GCP). Excellent communication skills and More ❯

/ML solutions in production environments Excellent communicator, comfortable working directly with clients and multidisciplinary teams Hands-on experience with MLOps tools such as MLflow, DVC, Kubeflow, Docker/Kubernetes, and GitOps practices Strong working knowledge of Azure and Databricks services Proficient with observability and monitoring tools (e.g. Prometheus, Grafana More ❯

Azure): Experience deploying AI solutions on cloud platforms. Python: Proficient in writing clean, production-quality code. AI Model Management: Familiarity with platforms such as MLFlow, Hugging Face, or LangChain. Data Processing: Experience with Databricks/Spark. SQL: Solid querying and data preparation skills. Data Architectures: Understanding of modern data systems More ❯

Azure): Experience deploying AI solutions on cloud platforms. Python: Proficient in writing clean, production-quality code. AI Model Management: Familiarity with platforms such as MLFlow, Hugging Face, or LangChain. Data Processing: Experience with Databricks/Spark. SQL: Solid querying and data preparation skills. Data Architectures: Understanding of modern data systems More ❯

risk, compliance or security-focused role. Strong proficiency in Python and statistical analysis. Familiarity with LLMs, ML pipeline management and AI lifecycle tools (e.g., MLflow, ModelOps platforms). Excellent communication and documentation skills for technical and non-technical stakeholders. Bachelor’s or Master’s degree in Machine Learning, AI, Computer More ❯

days per week (right to work in the UK required). Nice‐to‐haves Clinical or health‐tech domain knowledge. MLOps tooling (MLflow, Kubeflow, Vertex Pipelines). Benefits Competitive salary and attractive equity in a high growth startup 25 days holiday + UK bank holidays. Flexible hours & focus on sustainable More ❯

Natural Language Processing and Computer Vision Strong grasp of basic probability concepts and machine learning lifecycle Experience with workflow and pipelining frameworks (e.g., Kubeflow, MLFlow, Argo) Understanding and application of Ethical AI considerations Ready to take your career to the next level? Apply today and be part of something extraordinary More ❯