16 of 16 Permanent MLflow Jobs in the Thames Valley

workflows. ML Ops & deployment: Familiarity with deploying models into production using APIs or microservices, and applying ML Ops practices such as experiment tracking (e.g., MLflow, Weights & Biases), model versioning, and performance monitoring. Experience collaborating with engineering teams to ensure scalable and maintainable deployment. Backend & service development: Experience building production-grade ...

GenAI/LLMs: OpenAI API, Hugging Face Transformers, LangChain, Langraph, RAG pipelines Data & Analytics: Pandas, NumPy, Spark, Databricks, Hadoop, Vector Databases, Snowflake Model Deployment: MLflow, FastAPI, Flask, Docker, Kubernetes Cloud & Infrastructure: AWS, Azure, GCP CI/CD pipelines (GitLab, Jenkins) Desirable Skills Experience with prompt engineering, fine-tuning LLMs ...

platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35) Initial ...

platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35) Initial ...

platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35) Initial ...

Azure) and containerisation (Docker, Kubernetes) Solid understanding of ML fundamentals (model training, evaluation, common architectures) Desired Skills (Bonus Points) Experience with MLOps tooling (MLflow, Kubeflow, Weights & Biases, or similar) Building data pipelines (real-time or batch) using tools like Apache Spark, Kafka, Airflow, or dbt Familiarity with recommender systems, transformers ...

models in production environments. Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure). Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines. Excellent leadership, communication, and cross-functional collaboration skills. Bachelor's or Master's in Computer Science, Engineering ...

vector databases and embedding stores, including Pinecone, Weaviate, Milvus, FAISS, ChromaDB, and pgVector. Implement LLMOps/PromptOps practices using tools such as: Weights & Biases, MLflow, LangSmith, LangFuse, PromptLayer, Humanloop, Helicone, Arize Phoenix Benchmark, evaluate, and monitor LLM systems using RAGAS, DeepEval, custom eval suites, and human-in-the-loop review. ...

pipelines for analytics and modelling workflows. Model development & deployment: Familiarity with deploying models into production environments, collaborating with engineering teams, and using tools like MLflow or Weights & Biases for experiment tracking and reproducibility. Proof of work in cloud environments, especially MS Azure, is a plus. Research mindset with business impact ...

time normally, but may occasionally exceed 50% if required). Nice-to-Have: • Built agentic workflows/LLM tool-use. • Experience with MLFlow, Arize, LangFuse, or other MLOps tools. • Experience with deploying ML models on SageMaker, KServe, or similar. Why Plexe? • Hard problems: we're automating the entire ML/ ...

/or Agentic Systems, from development to production. Hands-on experience with LLM frameworks (e.g. langchain, langgraph, llamaindex, langsmith), AI platforms (e.g. Databricks, mlflow) and containerization solutions (e.g. Docker) is valued. Strong software engineering fundamentals and proficiency in Python are a must. Be creative, ambitious and curious. Be resourceful ...

/or Agentic Systems, from development to production. Hands-on experience with LLM frameworks (e.g. langchain, langgraph, llamaindex, langsmith), AI platforms (e.g. Databricks, mlflow) and containerization solutions (e.g. Docker) is valued. Strong software engineering fundamentals and proficiency in Python are a must. Be creative, ambitious and curious. Be resourceful ...

/or Agentic Systems, from development to production. Hands-on experience with LLM frameworks (e.g. langchain, langgraph, llamaindex, langsmith), AI platforms (e.g. Databricks, mlflow) and containerization solutions (e.g. Docker) is valued. Strong software engineering fundamentals and proficiency in Python are a must. Be creative, ambitious and curious. Be resourceful ...

Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student), LMS (Moodle/Canvas … prompt engineering), data pipelines, APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools (e.g., MLflow, Azure ML, Databricks, SageMaker or Vertex) plus observability practices. Familiarity with higher education processes and integrations across SIS, LMS, CRM, and ERP environments. Knowledge ...

Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student), LMS (Moodle/Canvas … prompt engineering), data pipelines, APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools (e.g., MLflow, Azure ML, Databricks, SageMaker or Vertex) plus observability practices. Familiarity with higher education processes and integrations across SIS, LMS, CRM, and ERP environments. Knowledge ...

Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student), LMS (Moodle/Canvas … prompt engineering), data pipelines, APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools (e.g., MLflow, Azure ML, Databricks, SageMaker or Vertex) plus observability practices. Familiarity with higher education processes and integrations across SIS, LMS, CRM, and ERP environments. Knowledge ...