1 to 25 of 28 Permanent MLflow Jobs in the UK

pipelines Containerization (Docker, Kubernetes desirable) Model packaging and REST APIs Cloud & Tools (Any combination) AWS/Azure/GCP analytics and ML services MLflow, Azure ML, SageMaker, Vertex AI Version control (Git) Domain & Soft Skills Strong analytical and problem solving skills Ability to explain complex data science concepts in simple ...

efficient deployments using Docker, Kubernetes (AKS/EKS/GKE), and Terraform/Bicep. Lead enterprise MLOps capabilities using Azure ML, SageMaker, Vertex AI, MLflow, and Kubeflow, integrated with CI/CD (GitHub Actions, Azure DevOps, Jenkins, Argo CD). Oversee observability and monitoring using Prometheus, Grafana, ELK/ ...

statistical evaluation Proven track record transitioning models from experimentation to production with appropriate governance and quality controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures It Would Be Great If You Also ...

FAISS, Milvus) Knowledge graphs and semantic search Data engineering pipelines MLOps & Deployment CI/CD for ML, model monitoring, versioning Kubernetes, Docker, serverless architectures MLflow, Kubeflow, SageMaker or similar Cloud & Architecture Azure AI, AWS AI/Bedrock, Google Vertex AI API-led architectures and microservices Security, governance, and responsible ...

pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Exposure to LLMOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc. Knowledge of Langchain, huggingface and LLM offerings by 3rd party vendors. Knowledge of OO programming and software design, i.e., SOLID principles. Knowledge ...

methodologies . Experience building production-grade AI systems using Python and ML frameworks (PyTorch, TensorFlow). Knowledge of MLOps/LLMOps practices and tooling (MLflow, Kubeflow, Docker, Kubernetes). Experience delivering AI solutions on AWS, Azure or GCP Experience leading or mentoring teams of AI engineers or data scientists. Robert ...

experience with core GenAI frameworks (e.g., LangChain, LlamaIndex) and Agentic AI frameworks (e.g., AutoGen, CrewAI, LangGraph). Proficiency in MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Strong working knowledge and practical deployment experience on major cloud platforms (AWS, Azure, GCP), including their AI/ML services. Strong foundation ...

XGBoost, LightGBM, or CatBoost. Experience with model deployment tools (e.g., ONNX, TensorRT, TensorFlow Serving, TorchServe). Familiarity with ML lifecycle tools such as MLflow, Kubeflow, or Azure ML Pipelines. Experience working with distributed data processing (e.g., PySpark) and SQL. Understanding of software engineering best practices, including version control (Git). ...

scalable, maintainable, and production-ready AI systems. Proficiency in Python with AI/ML frameworks (PyTorch, TensorFlow). Experience with MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Deep proficiency in Python and extensive experience with relevant AI/ML/NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK ...

frameworks like AutoGen, CrewAI or LangGraph . Experience building RAG architectures with vector databases (Pinecone, Weaviate, FAISS). Strong understanding of MLOps/LLMOps (MLflow, Kubeflow, Docker, Kubernetes). Experience deploying AI solutions on AWS, Azure or GCP . Solid software engineering and full-stack development experience in enterprise environments. ...

teams and delivering enterprise-grade data solutions. Preferred Qualifications Databricks certifications (e.g., Databricks Certified Data Engineer Professional, Architect ). Experience building ML solutions using MLflow or integrating with cloud ML services. Experience in BFSI, Retail, Telecom, or Healthcare data environments. Experience with real-time data processing (Kafka, EventHub, Kinesis). ...

learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g., MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures Ability to absorb complex scientific and technical concepts ...

deploying complex data solutions on the Microsoft Azure platform Experience collaborating with a range of stakeholders to structure data for downstream consumption (e.g. MLflow, Power BI semantic models) Infrastructure-as-code experience with Terraform for Azure resource provisioning Desirable Technical Skills Familiarity with streaming data architectures (Spark Structured Streaming) Knowledge ...

stack (pandas, scikit-learn, Jupyter, etc.) and version control tools like Git. Exposure to LLMOps, model monitoring, CI/CD and related technologies (Docker, MLflow, Kubernetes, FastAPI, etc.). Knowledge and working experience of AGILE methodologies. At Ageas we offer a wide range of benefits to support you and your ...

only. KEY SKILLS AI, Python, Machine Learning, Software Engineering, Data, APIs, Cloud, Agile, Python, TensorFlow, PyTorch, Scikit-learn, XGBoost, NLTK, OpenAI, LangChain, Pandas, NumPy, MLflow, Kubeflow, Docker, Kubernetes, Azure Machine Learning, Google Vertex ...

Strong experience in at least one - Azure, AWS Very Nice to Have: • Databricks certifications (Data Engineer Associate/Professional) • Experience with Feature Store/MLflow • Exposure to Databricks AI/Mosaic AI/Model Serving If you’re interested in building high-performance Databricks platforms at scale, send your ...

Knowledge of SQL and/or NoSQL databases AI/Machine Learning Exposure to ML/AI workflows or data science tooling Experience with MLflow or model tracking systems Scientific/Data Applications Experience working with scientific or bioinformatics datasets Exposure to single-cell RNA-seq, DNA/RNA sequences ...

Processing (NLP) and Computer Vision techniques Strong understanding of probability concepts and the machine learning lifecycle Experience with workflow and pipelining frameworks (e.g., Kubeflow, MLFlow, Argo) Awareness and application of Ethical AI principles This role offers a unique opportunity to work on cutting-edge projects, expand your expertise, and contribute ...

test splits are dangerous in time series and what to do about it. MLOps & Productionisation. Experience taking models from notebook to production: experiment tracking (MLflow, W&B), model versioning, feature stores, drift detection, and retraining triggers. You can build a model that doesn't just work once - it works reliably ...

Do you enjoy building infrastructure that powers complex engineering environments? Are you the type of engineer who loves improving performance, reliability and scalability across distributed systems? Looking for a role where your platform work directly ...

earth team What they're looking for: Solid experience with Databricks (Azure or AWS) Good understanding of tools like Delta Lake, Unity Catalog, MLflow Strong SQL and Spark (Python or Scala) Experience working with data pipelines and modern data platforms A good grasp of data modelling, warehousing, and general data ...

similar ML frameworks. Experience handling large datasets and distributed processing with PySpark or similar is desirable . Experience of experimentation tools such as MLflow is a bonus. Comfort with deploying ML models into production environments. Familiarity with AWS or similar cloud vendor . A methodical, problem-solving mindset with high ...

similar ML frameworks. Experience handling large datasets and distributed processing with PySpark or similar is desirable . Experience of experimentation tools such as MLflow is a bonus. Comfort with deploying ML models into production environments. Familiarity with AWS or similar cloud vendor . A methodical, problem-solving mindset with high ...

have a good knowledge of modern software engineering best practices, microservices, TDD/DDD, common Design Patterns Experience with Databricks, PostgreSQL, Amazon RedShift or MLflow would be great but not essential What's in it for you: As a Python Software Engineer (Machine Learning AWS) you will earn a competitive ...

training frameworks (DDP, FSDP, DeepSpeed). Background in NLP tasks such as NER, semantic similarity, QA, or dialogue systems. Experience with experiment tracking platforms (MLflow, Weights & Biases). Exposure to agentic AI paradigms (ReAct, chain-of-thought reasoning, tool use). Prior experience in leading AI research labs or high ...