1 to 25 of 83 Permanent MLflow Jobs in England

experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). What we offer Culture of caring: At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level More ❯

experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). What We Offer Culture of Caring: At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level 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 ❯

cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Hands-on experience with CI/CD pipelines, version control, and ML workflows (MLflow, Kubeflow). Proven track record of delivering ML models that solve real-world business challenges at scale. Excellent communication skills with the ability to work More ❯

cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Hands-on experience with CI/CD pipelines, version control, and ML workflows (MLflow, Kubeflow). Proven track record of delivering ML models that solve real-world business challenges at scale. Excellent communication skills with the ability to work 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 ❯

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 ❯

DS libraries (Scikit-learn, Numpy, LightlGBM, Pandas, LangChain/LangGraph, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc. MLOps: Terraform, Docker, Airflow, MLFlow More information: Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy, 2-for-1 share purchase plans, extra festive time 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 ❯

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 ❯

/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 ❯

/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 ❯

efficient data pipelines to handle text and audio data processing for ML models Deploy NLP models in cloud environments (AWS SageMaker) through Jenkins Use MLflow and other ML Ops applications to streamline ML workflows and adhere to data privacy and residency guidelines Communicate your work throughout the team and related 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 ❯

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 ❯

Evidently, etc.) Experience in building parallelised or distributed model inference pipelines Nice-to-Have Skills Familiarity with feature stores and model registries (e.g. Feast, MLflow, SageMaker Model Registry) Knowledge of model versioning , A/B testing , and shadow deployments Experience implementing or contributing to MLOps frameworks and scalable deployment patterns 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 ❯

large-scale models. Solid programming skills in Python and familiarity with machine learning frameworks like TensorFlow, PyTorch, Hugging Face Transformers, and MLOps tools (e.g., MLflow, Kubeflow). Strong analytical and problem-solving skills, with an aptitude for translating complex theoretical research into practical applications. Day to Day Conduct research and More ❯

with unit and integration tests Strong understanding of machine learning algorithms and best practices Vision for MLOps best practices, particularly regarding version control, Docker, MLFlow, CI/CD Strong communication skills, with the ability to engage effectively with diverse stakeholders Good commercial understanding; knowledge of marketing operations is a bonus 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 ❯