101 to 125 of 178 MLflow Jobs in the UK

exposure to Spark or similar data processing tools You may also have some familiarity with DevOps or MLOps tools such as Docker, Terraform or MLflow Ideally, you will have an interest in agile ways of working and CI/CD practices, though this is not essential More information: Enjoy fantastic ...

e.g., Git) and collaborative development Experience in using computing environments Strong problem-solving skills and willingness to learn Desirable: Familiarity with MLOps tools (e.g. MLflow, Weights & Biases) Exposure to natural language processing (LLMs, agents), computer vision, or reinforcement learning We actively recruit citizens of all backgrounds, but the nature ...

Triton, vLLM, or similar) with real latency and cost constraints(preferred RayServe) MLOps pipeline tooling - training pipelines, model registries, feature stores, and lineage (Kubeflow, MLflow, Feast, Weights & Biases, or equivalents) LLMOps in production - inference serving, prompt/version management, and LLM observability (tracing, evals, drift, guardrails, cost per request) Governing ...

Gemini, Claude and OpenAI APIs. Hands-on experience with AI tools/frameworks (e.g., Braintrust, AutoEval) and/or MLOps tools (e.g., Airflow, MLflow, Vertex AI, or similar). Solid understanding of data engineering practices, including ETL, batch/streaming pipelines, and data quality monitoring. Familiarity with cloud infrastructure ...

experience with LLMs and agentic systems[Preferred] Hands-on experience with technologies in the modern AI/LLM ecosystem, such as Databricks, Langchain, or MLFlow[Preferred] Advanced understanding of the probabilistic systems underpinning modern LLMs[Preferred] Experience building AI products in highly accuracy-sensitive domains such as finance ...

Autoloader) Programming skills inPython,SQL, orScala Proficiency indata modelling, ETL/ELT processes, and data architecture Experience in MS Copilot, AI Foundry , Databricks (MosiacAI, MLflow, Agentbricks, Genie) Strong analytical background with problem-solving skills Performance tuning concepts like watermarking, late data handling, parallelism & checkpointing Hands-on expertise inADF, and Qlik ...

with a clear focus on engineering and productionising machine learning modelsStrong hands-on development skills across Python, PySpark and SQLCommercial experience working with Databricks, MLflow and Delta LakeProven experience building and operating distributed data and machine learning pipelinesExperience taking Data Science models from notebooks or development environments into productionStrong understanding ...

client travel. Preferred Qualifications Experience conducting formal estate assessment, discovery, or technical due diligence work. Experience with MLOps or model lifecycle tooling such as MLflow, model registries, or feature stores. Experience with workflow orchestration tools such as Airflow, dbt, or Databricks Workflows. Experience with data product or data mesh operating ...

audiences Preferred qualifications, capabilities, and skills Experience with agent frameworks and protocols (MCP, A2A, Google ADK, LangGraph) and agent evaluation practices Experience with Databricks, MLflow, and model serving on Kubernetes in AWS Experience delivering AI systems through model risk management or equivalent regulatory review Experience running a team within ...

. Familiarity with observability tooling (Prometheus, Grafana, OpenTelemetry) and with exposing it for third‐party components. Exposure to ML orchestration tooling (Flyte, Airflow, MLflow, SkyPilot). Go, and a track record of contributing to open‐source infrastructure projects. Perks & Benefits Indefinite contract. Variable performance bonus. Signing bonus. We offer work ...

English. Preferred Qualifications, Capabilities & Skills Product management experience for AI/ML, MLOps, or data platforms. Familiarity with MLOps concepts and frameworks, such as MLflow, Amazon SageMaker, and feature stores. Familiarity with AI concepts, such as Retrieval‐Augmented Generation (RAG), agentic system architectures, evaluation of LLMs and agents, and Model ...

learning, on-prem, or air-gapped deployment experience. Experience building self-serve ML platforms or tools for non-expert users. Experience with lakeFS, DVC, MLflow, Weights & Biases, Kubernetes, Kubeflow, Flyte, Dagster, Airflow, or Argo. LLM application, context engineering, structured output, or LLM evaluation experience. Exposure to radar, AIS, EO/ ...

lifecycle management Developer experience: APIs, SDKs, CLIs, notebooks Infrastructure: storage, networking, IAM, observability, infrastructure-as-code Familiarity with tools such as PyTorch, Ray, Slurm, MLflow, Langchain, Hugging Face, vLLM, Triton, or similar. Able to balance performance, cost, usability, flexibility, and reliability. Strong prioritisation, communication, and stakeholder management skills. Comfortable taking ...

with MongoDB or other NoSQL databases Experience with unsupervised methods such as clustering or hidden Markov models Experience with ML lifecycle tooling such as MLflow Experience with anomaly detection A background around boats, cars, bikes or planes We're less interested in ticking off niche experience like maritime or MongoDB ...

equivalent — and familiarity with what good looks like across different GPU generations and topologies. Exposure to MLOps tooling and AI platform layers: experiment tracking (MLflow, W&B), model serving frameworks (Triton, vLLM), and pipeline orchestration (Kubeflow, Airflow). Familiarity with InfiniBand and high-performance networking as it relates to distributed ...

binary classification problems Event streaming data engineering tools such as Flink or Spark Experience with MLOps and tools such as Airflow, BentoML and MLFlow Use of Docker CI/CD and SDLC (e.g. JIRA, Git, Jenkins, Octopus) Job type Permanent Skills DataScientist Why Zempler Bank We’re on a journey ...

Intact Insurance, the UK arm formerly RSA, is recruiting a Machine Learning Engineer to build and run production-ready ML systems that impact the business. You will collaborate with Data Scientists and engineering teams, shaping ...

product engineering—from architectural design and prototyping to CI/CD-enabled deployment—using modern platforms and tools such as Azure ML, Databricks, MLflow, LangChain and LangGraph. Champion automation, testing, and observability across pipelines.· Operational Excellence: Define reusable development patterns, enforce coding standards, and promote MLOps best practices that support … e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers).· Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph.· Proven experience with modern engineering practices Git, version control, unit testing and containerisation.· Familiarity with agile work methodologies and tools like Jira ...

ambiguity. Desirable MLOps excellence: reproducible pipelines, model versioning, CI/CD, observability, and automated evaluation. Data engineering: proficiency with Databricks, Apache Spark, Delta Lake, MLflow, and SQL; experience integrating datasets and maintaining data quality. Model training and optimisation: experience with pre‐training, fine‐tuning, distributed training, inference optimisation or adapting … Education: PhD in AI/ML/CS or related field. Beneficial knowledge General tooling and platforms: Databricks, AWS, GCP, GitHub, Docker/Kubernetes, MLflow, Jira. Edge deployments: Nvidia Jetson (e.g. AGX Orin), Raspberry Pi, or other embedded accelerators. Distributed model training & infra: Pytorch DDP, FDSP and TorchTitan, Megatron, Slurm ...

ixolabs.ai is seeking an MLOps Engineer for AI training to build scalable pipelines, registries, and rollback plans. You will review code across Kubeflow, MLflow, SageMaker, Vertex AI & Azure ML and improve CI/CD for ML workflows. Ideal candidates bring multiple cloud ML platform strengths, Docker/Helm proficiency ...

ideal Machine Learning Engineer candidate will have: Highly skilled in Python. Knowledge of AWS or GCP. Ideally experience of SKLearn/Docker/MLFlow or PyTest Excellent communication and problem solving skills. What is in it for you? As a talented Machine Learning Engineer you can expect: Great salary ...

teams. You Need Expert Python and SQL, with experience building production ML systems and data pipelines (PyTorch, XGBoost, Spark/PySpark, Apache Iceberg, Ray, MLflow, SageMaker, Airflow, or equivalent). Deep experimentation and statistical inference skills, and a strong grasp of optimisation under uncertainty (bandits, causal inference, off-policy evaluation ...

Terraform Monitoring and performance tuning of cloud-based applications and services Nice to haves: (MLOps): Model Deployment & Serving – Deploy and manage ML models using MLflow, Azure ML, SageMaker, or similar, ensuring scalability and performance. Monitoring & Retraining – Set up model drift detection, performance monitoring, and automated retraining ML Pipelines & CI/ ...

multiple layers Preferred Qualifications, Capabilities, and Skills: Experience with agent frameworks and protocols (Google ADK, LangGraph, MCP, A2A, AG-UI) Experience with Databricks, MLflow, Spark, and Delta Lake or Apache Iceberg Experience serving models on Kubernetes, including GPU workloads and fine-tuned small language models Experience with optimization or pricing ...

metrics. Experience creating, managing, and interrogating graph databases (e.g., Neo4j). Experience with maritime, aerial, or other remote-sensing imagery. Exposure to MLOps tools (MLflow, Weights & Biases, Ray etc.) Experience deploying systems with containerisation, both on premises and in the cloud (e.g. using Docker and AWS ECS/ ...