19 of 19 Remote/Hybrid MLflow Jobs in England

scale LLM and generative AI tooling exposure (LangChain, LlamaIndex, vector databases such as Pinecone, Weaviate or pgvector, RAG patterns, fine-tuning workflows) MLOps platforms (MLflow, Kubeflow, Vertex AI, SageMaker, Databricks or equivalent) Cloud experience (AWS, GCP, Azure), containerisation and basic data engineering/SQL Familiarity with experimentation, A/ ...

solutions within document-heavy environments such as legal, financial services, insurance or similar enterprise organisations would be highly advantageous Experience with Docker, Kubernetes, MLflow, CI/CD and Git-based development Strong communication skills with the ability to work across technical and non-technical teams This is an excellent opportunity ...

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 ...

Factory, Synapse, Databricks, ADLS Gen2, Event Hub, Purview AWS: S3, Glue, Athena, Kinesis, Lambda, EMR, Lake Formation Databricks: Delta Lake, Unity Catalog, Structured Streaming, MLflow SQL Server stack (SSIS, SSRS) Engineering Practices CI/CD for data platforms and Infrastructure-as-Code (Terraform/Bicep) Git, monitoring and alerting tools ...

related technical discipline. Bonus Skills/Experience Public writing, talks, or threads about building with AI. MLOps and model serving experience (BentoML, MLflow, Vertex AI, SageMaker). Streaming and batch ingestion pipelines (Spark, Airflow, Beam, Glue). Healthcare or life sciences domain exposure. AWS Professional certification or other relevant industry ...

analytical programming and visualisation languages and libraries (SQL, python, matplotlib, etc.) as well as some of the supporting tools and platforms (e.g. git, MLFlow, Kubernetes, Kubeflow, Trino, AirFlow). A strong understanding of statistical concepts (hypothesis testing, sampling, probability distributions). Excellent communication and collaboration skills to effectively bridge ...

analytical programming and visualisation languages and libraries (SQL, python, matplotlib, etc.) as well as some of the supporting tools and platforms (e.g. git, MLFlow, Kubernetes, Kubeflow, Trino, AirFlow). A strong understanding of statistical concepts (hypothesis testing, sampling, probability distributions). Excellent communication and collaboration skills to effectively bridge ...

infrastructure (Multi‐node GPU training, Kubernetes, vLLM). Familiarity with Deep Learning frameworks (PyTorch). Experience with MLOps tools and experiment tracking (e.g., ClearML, MLFlow, Weights & Biases). Research Fluency: Ability to read technical research papers and translate them into engineering requirements. You don’t need to write the paper ...

Data Scientist: Experience with deep learning frameworks advanced modelling techniques Familiarity with MLOps concepts model monitoring deployment pipelines Exposure to tools such as Databricks MLflow feature stores Experience working in Agile product-led delivery environments Understanding of data governance ethics model explainability Relevant professional certifications relating to cloud data platforms ...

Experience with Python-based data and ML tooling, e.g. Pandas, NumPy and scikit-learn Experience with ML tooling within Microsoft Fabric or Azure, e.g. MLflow, notebooks, SynapseML or equivalent Ability to structure data for AI/ML use and integrate outputs into business processes Proven ability to assess, design ...

data engineers and platform teams to raise standards for CI/CD, experiment tracking, and model lineage. You’ll design scalable Databricks workflows, champion MLflow usage, implement secure, auditable promotion across environments and mentor the team to deliver business value at scale. #J-18808-Ljbffr ...

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 Senior Machine Learning Engineer (Python AWS) you will earn a competitive ...

Model optimisation/deployment tooling (ONNX, TensorRT) Edge deployment experience (e.g., NVIDIA Jetson or other resource-constrained devices) Familiarity with MLOps tooling (e.g., DVC, MLflow) Relevant open-source contributions in computer vision Interested? If this sounds like you, apply with your CV or get in touch to discuss the role ...

Exceptional command of the English language Nice-to-Have We’d also love experience with: Version control for data and artefacts: DeltaLake DVC MLFlow Designing and operating cloud-based systems AWS and/or Databricks Messaging platforms Infrastructure as Code tools such as: Terraform CloudFormation Pulumi Kubernetes and service mesh ...

context, including orchestration patterns, tool use, memory management, and agent reliability at scale Familiarity with one of the major AI ecosystems, such as LangSmith, MLflow, or Databricks ML Having navigated a transition from a scrappy, point-to-point AI integration to a well-engineered, reusable AI platform. An understanding ...

large and complex datasets, both structured and unstructured Write clean, scalable Python code for model development and production use Use tools such as Databricks, MLflow and modern AI platforms to manage the full model lifecycle Translate technical outputs into clear, commercially relevant insights Engage directly with stakeholders to define problems … practical understanding of how to apply LLMs to real-world use cases Tools & Engineering Experience with model deployment and MLOps tools (e.g. Databricks, MLflow) Familiarity with version control (Git) and collaborative development practices Awareness of best practices in code quality and reproducibility Communication & Consulting Ability to explain complex technical concepts ...

Description Join us, be part of more. We're so much more than an energy company. We're a family of brands revolutionising how we power the planet. We're energisers. One team of 21 ...

model governance committee: chairing review meetings, escalating high-risk models and producing governance metrics for risk committees and regulators• Build model governance tooling: integrating MLflow, Azure ML or Databricks with governance workflows, automated testing and regulatory reportingRequired Skills & Experience:• 7+ years of model risk management, quantitative risk or ML engineering … applied to ML models• Hands-on Python skills: you can read model code, run validation analyses and build monitoring scripts — not just review documentation• MLflow, Azure ML or Databricks experience for model lifecycle management• Regulatory knowledge in at least one sector: financial services (preferred), healthcare, insurance or utilities• Strong statistical ...

Job Title: DevOps Engineer Location: Durrington, hybrid Contract Type: Permanent Hours: 37 per week Salary: from £50k About the role We're looking for a forward-thinking DevOps Engineer to play a key role in ...