76 to 100 of 121 MLflow Jobs in England

retraining Experience leading or mentoring engineering squads Hands‐on experience building and training deep learning models in PyTorch Familiarity with MLOps tooling such as MLflow and CI/CD workflows Experience with AWS, Azure, or GCP Experience with sequence models (e.g. transformers, RNNs) or generative models (e.g. diffusion, flow ...

retraining Experience leading or mentoring engineering squads Hands‐on experience building and training deep learning models in PyTorch Familiarity with MLOps tooling such as MLflow and CI/CD workflows Experience with AWS, Azure, or GCP Experience with sequence models (e.g. transformers, RNNs) or generative models (e.g. diffusion, flow ...

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 ...

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 ...

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 ...

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 ...

Python and proficiency in other languages (e.g., SQL, R, Java). Strong experience deploying and monitoring machine learning (MLOps) using tools such as MLflow, AWS Sagemaker, and Azure Machine Learning. Proven track record of delivering high-quality, scalable data science solutions. Expertise in Data Manipulation, ML, and Statistical Analysis coding ...

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 ...

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 ...

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 ...

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 ...

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/ ...

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/ ...

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/ ...

Managed Services on cloud and on prem AI/ML & MLOps - Open source AI/ML solutions, AIOps automation, model lifecycle management, Kubeflow, MLFlow, KServe, and AI infrastructure on cloud and edge IoT - Ubuntu on embedded devices and/or edge servers, device management, and robotics Cloud - Ubuntu in public ...

Intact Insurance is actively seeking a Machine Learning Engineer to design and operate production-ready ML systems. You will collaborate with Data Scientists and engineers to shape the ML roadmap, build scalable pipelines, and drive ...

Intact Insurance is actively seeking a Machine Learning Engineer to design and operate production-ready ML systems. You will collaborate with Data Scientists and engineers to shape the ML roadmap, build scalable pipelines, and drive ...

business impact. The candidate will have experience with AI deployments across cloud platforms like Azure and AWS, and familiarity with frameworks such as MLflow and Kubeflow. Flexible working arrangements are available, reflecting the company's commitment to employee wellbeing. #J-18808-Ljbffr ...

RoCEv2, Spectrum-X, and fabric management. Solid expertise with Kubernetes, OpenShift, containerized workloads, GPU orchestration platforms, and AI/ML technologies such as Kubeflow, MLflow, JupyterHub, Run:AI, Rafay, ClearML, and MLOps solutions. Experience with HPC workload scheduling and resource management tools such as Slurm and PBS Pro, as well ...

Deployment (MLOps): Partner with our engineers to transition your models from prototype into scalable, monitored, and reliable production pipelines using tools like MLflow and Optuna. Your Skills Strong hands-on professional experience in Data Science, successfully building and deploying systems from prototype to production in a fast-paced environment. Strong … handling columnar data formats like Parquet. MLOps Exposure: Experience with tools and frameworks for training, tracking, deploying, and monitoring models in production (e.g., MLflow, Optuna, Prefect, or Airflow). Background in supply chain forecasting, enterprise AI, or retail analytics M.S. or Ph.D. in Computer Science, Artificial Intelligence, Statistics, Data Science ...

evaluation. Build hands-on proofs of concept and reference implementations that operationalise large-scale LLM and deep learning workloads on Databricks (Mosaic AI, MLflow, Model Serving, Vector Search, Unity Catalog governance), tuned to the fast iteration cycles Emerging DNB customers expect. Lead fine-tuning and model-customisation engagements on open … distributed training, GPU workloads, and the full MLOps lifecycle (tracking, registry, serving, monitoring). Proficiency in Python and the ML ecosystem (PyTorch/Transformers, MLflow, Spark), and comfort building production-quality reference implementations. Experience with the Databricks platform — or the ability to ramp on it quickly — including Mosaic AI, Model ...