1 to 25 of 64 Remote/Hybrid MLflow Jobs in the UK

GenAI frameworks (e.g., LangChain, Hugging Face) and cloud-native AI services (AWS, Azure or GCP) Knowledge of MLOps practices and tools like Databricks or MLflow Ability to tackle ambiguous problems with structured, analytical approachesStrong verbal and written communication skills for technical and executive audiences Experience in hybrid consulting environments, balancing ...

Studio, OpenAI, AKS), GCP (Vertex AI, Cloud Run), AWS (Bedrock, SageMaker)* Experience building and automating AI/ML pipelines using tools such as MLflow, Kubeflow, Azure ML, Vertex Pipelines, Airflow or Google ADK* Hands-on experience with Generative and Agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, Autogen, Google ...

Science, Machine Learning, or related field Nice to Have Published research in top ML venues (NeurIPS, ICML, ACL, CVPR). Experience with MLOps tools: MLflow, Weights & Biases, DVC. Familiarity with distributed training frameworks (DeepSpeed, Horovod). Experience with LLM fine-tuning and prompt engineering. Contributions to open-source ML projects. ...

functional teams. Desirableskills andexperience: Experience building platforms or applications that support Data Science, Machine Learning, or AI workloads. Experience with MLOps tooling such as MLflow, Kubeflow, Vertex AI, or similar technologies. Knowledge of workflow orchestration platforms such as Apache Airflow. Experience with data processing technologies such as Pandas, Apache Beam ...

similar. Experience with MLOps practices such as model deployment, monitoring, versioning or model registries. Exposure to workflow orchestration or deployment tools such as Airflow, MLflow, Azure DevOps, GitHub Actions or similar. Experience in pricing, insurance, financial services or another regulated environment. Understanding of model governance, responsible AI or explainability. Interview ...

Strong proficiency in Python (pandas, scikit-learn, PyTorch/TensorFlow) and SQL, with experience in geospatial and environmental data analysis. Experience with MLOps tools (MLflow, Docker, CI/CD pipelines) and cloud platforms (Azure preferred), ensuring scalable and reliable solutions. Proven ability to influence non-technical stakeholders and communicate complex ...

E.g. test-driven development, smart data structure and algorithm selection. Experience in using cloud environment (e.g. Azure, AWS). Experience using Azure Databricks, Azure MLflow, Azure ML services and/or other ML services. Experience using Excel, SQL, Power BI, Tableau. Experience using Docker and Kubernetes. Experience working ...

solving skills and attention to detail Experience with LLMs and generative AI (OpenAI, Hugging Face, LangChain) Knowledge of NLP or computer vision Experience with MLflow, Kubeflow or similar MLOps tools What We Offer ✓ Competitive salary based on experience ✓ Diverse AI projects across multiple industries ✓ Collaborative and research-driven team environment ...

Candidates should have strong experience in AI Engineering, MLOps and cloud-native AI platforms, alongside hands-on knowledge of technologies such as LangChain, LlamaIndex, MLflow, Kubernetes, Docker and CI/CD tooling. Applicants will ideally demonstrate: Experience working in a major Consulting firm, and/or in industry A strong ...

Candidates should have strong experience in AI Engineering, MLOps and cloud-native AI platforms, alongside hands-on knowledge of technologies such as LangChain, LlamaIndex, MLflow, Kubernetes, Docker and CI/CD tooling. Applicants will ideally demonstrate: * Experience working in a major Consulting firm, and/or in industry * A strong ...

Fluent English – for international communication and collaboration. Additional Information Nice to have: Experience with LLMs, or Time Series, Familiarity with tools like Docker, MLflow, Airflow, AWS/GCP/Azure, Background in research or R&D, Experience working in cross-functional or international teams. Soft Skills: Curiosity and problem-solving ...

with technical and business stakeholders. Desirable Experience with Unity Catalog or similar data governance frameworks. Experience with Terraform or Databricks Asset Bundles. Exposure to MLflow, MLOps or AI and Generative AI workloads. Experience with streaming technologies such as Kafka or Structured Streaming. Databricks certification. Previous consulting or client-facing delivery ...

Solid grasp of MLOps principles with experience deploying models in production Proficiency in Python and tools/platforms such as Azure, AWS, GCP, Databricks, MLFlow, and Airflow Strong communication skills with the ability to engage business and technical stakeholders We offer EPAM Employee Stock Purchase Plan (ESPP) Protection benefits including ...

workloads in production (AWS or similar). Evaluation and observability for AI — hands‐on with tools like LangFuse, LangSmith, Braintrust, or MLflow — plus solid automated testing and CI/CD. Proven technical leadership — mentoring engineers, driving technical vision, and delivering complex, cross‐team projects. English — advanced proficiency, written and spoken. ...

enhance your day-to-day work. Technologies and Tools Python Machine learning frameworks (e.g. PyTorch, TensorFlow, scikit-learn) ML/MLOps tooling (e.g. SageMaker, MLflow, TFServing) Spark and Databricks AWS services (e.g. IAM, S3, Redis, ECS) CI/CD tooling and best practices Streaming and batch data systems (e.g. Kafka ...

OpenAI, AI Foundry or AI Search, with Docker and Kubernetes Understanding of schema validation frameworks (e.g., JSON Schema, Pydantic) and MLOps tools such as MLflow or Airflow Strong communication ability to explain trade-offs around cost, latency and accuracy to technical and non-technical audiences Nice to have Experience using ...

Comfortable working with technical and non-technical stakeholders to deliver high-quality solutions. Even better if you have Databricks certifications. Experience with Unity Catalog, MLflow or Databricks Asset Bundles. Familiarity with dbt or similar data transformation frameworks. Exposure to Kafka, Event Hubs or other streaming technologies. Experience working with retail ...

APIs, or cloud-native application deployment Experience with infrastructure as code, automated testing, observability, logging, or platform monitoring Awareness of MLOps concepts such as MLflow, model registry, model promotion, model monitoring, and governed deployment pipelines Exposure to machine learning workflows or data science environments, with an interest in developing into ...

with data engineers on performance optimization, cost control, and platform capabilities MLOps & AI Platform (20%) Build ML model deployment pipelines using Azure ML, Databricks MLflow, or both Implement model versioning, experiment tracking, and model registry patterns Establish inference endpoints (batch and real‐time) with proper monitoring and governance Create reusable ...

modelling, ETL and ELT processes, data quality, security and governance Ability to collaborate effectively with technical and non-technical stakeholders Experience with Unity Catalog, MLflow or Databricks Asset Bundles would be advantageous Knowledge of dbt, Kafka, Event Hubs or other data transformation and streaming technologies would be beneficial Desirable Experience ...

modelling, ETL and ELT processes, data quality, security and governance Ability to collaborate effectively with technical and non-technical stakeholders Experience with Unity Catalog, MLflow or Databricks Asset Bundles would be advantageous Knowledge of dbt, Kafka, Event Hubs or other data transformation and streaming technologies would be beneficial Desirable Experience ...

technical planning, architecture decisions and engineering best practices. Essential experienceStrong Python development skills. Experience with Machine Learning experiment tracking and model registries using MLflow, Weights & Biases, Neptune, ClearML or a similar platform. Experience with distributed training frameworks such as Ray, DeepSpeed, Horovod or PyTorch FSDP.Hands-on experience optimising models ...

observability (Ganglia, Prometheus, or Datadog). Understanding of serverless Databricks clusters. Familiarity with Terraform and infrastructure as code for Databricks resource management. Exposure to MLflow and model-serving pipelines for end-to-end performance optimization. Experience with Unity Catalog and fine-grained governance controls. Qualifications Bachelor's or Master ...

responsible AI practices are maintained. Experience Proven experience designing and delivering data and AI platforms using Databricks. Strong knowledge of Databricks Lakehouse, Unity Catalog, MLflow, and AI workloads. Experience developing GenAI solutions such as RAG, embeddings, and LLM integration. Experience designing agentic workflows and orchestration patterns. Strong understanding of Azure ...

version control. Experience with AI assisted tooling Hands-on experience taking machine learning models into production and supporting them once live. Experience with MLflow or similar model lifecycle tooling, including deploying models for batch and/or near real-time use cases. Experience building or working with CI/ ...