22 of 22 Remote/Hybrid MLflow Jobs

including sovereign, on-premise and hybrid deployment models. Proficiency in MLOps tools and practices: CI/CD, monitoring and orchestration frameworks (e.g. Kubeflow, Flyte, MLflow). Good knowledge of Docker and Kubernetes for containerizing AI workloads. Understanding of LLM inference stacks (vLLM, llama.cpp, OpenVINO) and model deployment formats (ONNX, .safetensors ...

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/ ...

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 ...

skills and a collaborative approach Nice to have Edge AI or embedded ML deployment (Jetson, Raspberry Pi, ARM or similar) Computer Vision Databricks, Spark, MLflow Docker, Kubernetes and AWS Experience working in defence, aerospace, robotics, autonomous systems or other safety-critical environments Current SC or DV clearance (although candidates eligible ...

LangGraph (agent architecture design, state management, and graph-based workflow orchestration). ML & Cloud Ecosystems: Solid understanding of ML algorithms, FastAPI, PyTorch/TensorFlow, MLflow, MLOps practices, containerization (Docker, Kubernetes/AWS EKS), and cloud services (AWS Bedrock, SageMaker, Azure AI Search). Soft Skills: Excellent communication and collaboration skills ...

Databricks, Azure ML, and ideally Azure AI Foundry Strong experience deploying and managing LLMs and machine learning models in enterprise cloud environments Experience using MLflow for experiment tracking, model lifecycle management, and versioning of both traditional ML models and LLM-based solutions Strong understanding of LLMOps practices, including deployment, monitoring ...

Enable AI/ML and analytics use cases: Prepare curated datasets and features, collaborate with data scientists, and integrate pipelines with ML workflows (e.g., MLflow) where required. Monitor and optimise jobs and clusters: Tune Spark performance, improve reliability, manage costs, and implement observability (logging, alerting, SLAs) for production workloads. Collaborate ...

lifecycle best practices Hands-on experience with ML libraries: PyTorch, PySpark, scikit-learn, Hugging Face Transformers Proficiency in AI tooling: Azure ML, Databricks, MLflow, LangChain, LangGraph Proven experience with Git, unit testing, containerisation and agile methodologies (Jira, Confluence) Good knowledge of generative AI, machine learning, deep learning or NLP Strong ...

with any of the following would be beneficial: AWS SageMaker, Bedrock, Lambda, ECS, EKS, Step Functions, EventBridge, CloudWatch, IAM, S3, ECR, or related services. MLflow, model registries, feature stores, model observability, drift detection, and automated retraining patterns. AIOps use cases such as anomaly detection, incident enrichment, automated ticket creation, event ...

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 ...

2+ years experience as data engineer on AI/ML project with Python Strong experience using Databricks, including Jobs, Asset Bundles, Delta Lake, and MLflow, as well as Azure data engineering tools such as Azure Data Factory and Azure Data Lake Storage (ADLS). Solid understanding of Scrum practices ...

certification in NLP, ML, or related fields. Familiarity with DevOps practices and tools. Hands-on experience with experimentation and model tracking tools (e.g., MLFlow, Weights & Biases). Demonstrable impact of technical solutions or projects on decision-making Experience working in fast-paced, agile environments. Customer-facing experience, notably in understanding ...

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 ...

integration/fine-tuning (OpenAI, LLaMA, Cohere, etc.) Strong coding in Python and experience with frameworks/tools such as FastAPI, PyTorch/TensorFlow, MLflow; 3-5+ years of experience in designing and developing scalable web applications using modern front-end frameworks such as React/TypeScript. Experience working ...

integration/fine-tuning (OpenAI, LLaMA, Cohere, etc.) Strong coding in Python and experience with frameworks/tools such as FastAPI, PyTorch/TensorFlow, MLflow; 3-5+ years of experience in designing and developing scalable web applications using modern front-end frameworks such as React/TypeScript. Experience working ...

design. Desirable (AI & Data) Vector DBs: Milvus, Weaviate, Pinecone Data orchestration: Airflow, Prefect, Dagster Search: ElasticSearch/OpenSearch AI frameworks: LangChain, Hugging Face MLOps: MLflow, Kubeflow If you are looking for an opportunity to work on mission-critical systems at the forefront of UK National Security? Apply ...

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 ...

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 ...

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 xkybehq earn ...

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 ...

automation Work within air-gapped environments, ensuring secure deployment of ML solutions Collaborate with data scientists to operationalise ML models Utilise tools such as MLflow and Airflow for model tracking and orchestration Support cloud-based deployments across AWS and Google Cloud Platform Ensure performance, reliability, and scalability of machine learning …/Linux Experience building CI/CD pipelines using GitLab (YAML) Understanding of DevSecOps principles and tooling Exposure to ML lifecycle tools such as MLflow and Airflow Ability to work in highly secure or air-gapped environments Strong problem-solving and collaboration skills What you'll get in return Opportunity ...

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 ...