201 to 225 of 323 MLflow Jobs in England

At Databricks, our core values are at the heart of everything we do; creating a culture of proactiveness and a customer-centric mindset guides us to create a unified platform that makes data science and analytics accessible to everyone. We More ❯

across the Group to identify and capture business requirements, which can then be met with advanced analytics and machine learning solutions. Design and develop analytical models (primarily using Databricks’ MLflow) on the cloud data platform following best practices for end-to-end model lifecycle (e.g. exploratory data analysis, model development, model training, model deployment and retraining) Maintaining a continual feedback … knowledge of technology architectures & processes involved in the modelling of data Strong coding experience in Python, in a data science context and a good grounding in SQL. Any Databricks, MLFlow and Spark experience would be advantageous. Up-to-date knowledge of data privacy & security standards in an Insurance context Comfortable with manipulating and analysing large datasets including data cleansing to More ❯

challenges into scalable solutions. We seek someone hands-on, curious, and eager to make a difference. You should have strong Python skills, particularly with the scikit-learn ecosystem and MLFlow, and be confident working with SQL on large datasets. A solid understanding of supervised and unsupervised learning techniques, as well as experience deploying models in cloud environments, is essential. Experience More ❯

based with the right to work and able to be in the office 2–3 days per week Nice to Have Background in healthcare, clinical tech, or MLOps tooling (MLflow, Kubeflow, Vertex Pipelines) What’s on Offer 💸 Competitive salary + meaningful equity 🧘‍♂️ 25 days holiday + UK bank holidays 🌱 Flexible hours and a sustainable work pace 🌇 Bright, collaborative office minutes More ❯

based with the right to work and able to be in the office 2–3 days per week Nice to Have Background in healthcare, clinical tech, or MLOps tooling (MLflow, Kubeflow, Vertex Pipelines) What’s on Offer 💸 Competitive salary + meaningful equity 🧘‍♂️ 25 days holiday + UK bank holidays 🌱 Flexible hours and a sustainable work pace 🌇 Bright, collaborative office minutes More ❯

based with the right to work and able to be in the office 2–3 days per week Nice to Have Background in healthcare, clinical tech, or MLOps tooling (MLflow, Kubeflow, Vertex Pipelines) What’s on Offer Competitive salary + meaningful equity ‍♂️ 25 days holiday + UK bank holidays Flexible hours and a sustainable work pace Bright, collaborative office minutes More ❯

to the delivery of complex business cloud solutions. The ideal candidate will have a strong background in Machine Learning engineering and an expert in operationalising models in the Databricks MLFlow environment (chosen MLOps Platform). Responsibilities: Collaborate with Data Scientists and operationalise the model with auditing enabled, ensure the run can be reproduced if needed. Implement Databricks best practices in More ❯

to the delivery of complex business cloud solutions. The ideal candidate will have a strong background in Machine Learning engineering and an expert in operationalising models in the Databricks MLFlow environment (chosen MLOps Platform). Responsibilities: Collaborate with Data Scientists and operationalise the model with auditing enabled, ensure the run can be reproduced if needed. Implement Databricks best practices in More ❯

to the delivery of complex business cloud solutions. The ideal candidate will have a strong background in Machine Learning engineering and an expert in operationalising models in the Databricks MLFlow environment (chosen MLOps Platform). Responsibilities: Collaborate with Data Scientists and operationalise the model with auditing enabled, ensure the run can be reproduced if needed. Implement Databricks best practices in More ❯

including shell scripting and performance tuning. Nice to have: Certifications in Kubernetes, Ceph, or cloud technologies (AWS/GCP/Azure). Familiar with with ML infrastructure: Ray (KubeRay), MLFlow, KubeFlow, Nexus (Pypi) or model serving platforms. Familiar with Git, GitOps workflows to aid the Infrastructure-as-code Experience with service mesh technologies like Istio. Willing to dabble in Python More ❯

around applying machine learning in healthcare, looking to push the boundaries of science! Desired experience: Ph.D. in a relevant area. Understanding of PyTorch, TensorFlow, and platforms like TFX, Neptune.ai, MLflow, Weights & biases, etc. Previous experience working in computer vision or machine learning. Knowledge of digital pathology. Awareness and prior experience in Life Science and/or computational biology. Following your More ❯

or graph models . Experience applying probabilistic models in real-world applications (e.g., recommendation systems, anomaly detection, personalized healthcare, etc.). Understanding of modern ML pipelines and MLOps (e.g., MLFlow, Weights & Biases).Experience with recent trends such as foundation models , causal inference , or RL with uncertainty . Track record of publishing or presenting work (e.g., NeurIPS, ICML, AISTATS, etc.) is More ❯

make a difference – and who brings the following: Strong Python coding skills. Proficiency with Azure and orchestration tools like Azure DevOps (ADO). Experience with MLOps frameworks such as MLflow, Kubeflow, Metaflow, or SageMaker. Experience deploying real-time inference services and batch prediction pipelines. Solid understanding of CI/CD practices and monitoring tools (e.g., Prometheus, Grafana). Benefits Our More ❯

frameworks and regulatory standards (e.g., PRA SS1/21, FCA PS21/3, DORA, NIST AI RMF). Experience with AI/ML platforms and monitoring tools such as MLflow, Azure ML, SageMaker, Databricks, Python. Excellent stakeholder management and communication skills. Desirable: Technical background in AI/ML, data science, or software engineering. Experience with cloud-native AI environments and More ❯

or graph models . Experience applying probabilistic models in real-world applications (e.g., recommendation systems, anomaly detection, personalized healthcare, etc.). Understanding of modern ML pipelines and MLOps (e.g., MLFlow, Weights & Biases). Experience with recent trends such as foundation models , causal inference , or RL with uncertainty . Track record of publishing or presenting work (e.g., NeurIPS, ICML, AISTATS, etc. More ❯

pressure. Nice-to-Have: Experience with marketing data or customer-level modelling (e.g., uplift, attribution, causal AI, graph AI, campaign optimization, spend optimization). Exposure to MLOps tools like MLflow, FastAPI, Airflow, or similar. Experience with experimentation and validation frameworks (e.g., A/B testing). Startup or freelance experience that required pace, clarity, and autonomy. Why This Role is More ❯

Collaborate with backend and platform engineering teams to identify technical gaps, scope backend development efforts, and deliver core platform capabilities such as: CI/CD for ML (e.g., using MLflow, Kubeflow, or Vertex AI Pipelines) Model versioning, monitoring, and governance Enable high-impact AdTech use cases including: Marketing Mix Modeling (MMM) Real-time personalization and bidding Audience segmentation and targeting More ❯

Fluency in English. Nice to haves (not mandatory): Expertise in geospatial data and mobility analytics; Experience with big data technologies like Spark and Kafka; Experience with ML pipeline tools (MLflow, Sagemaker) or building pipelines with Docker, Kubernetes, Airflow; Ph.D. in a quantitative field; Knowledge of the shipping industry and commodity trading; Familiarity with software engineering best practices; Commitment to code More ❯

frameworks and regulatory expectations (e.g., PRA SS1/21, FCA PS21/3, DORA, NIST AI RMF). Experience working with AI/ML platforms and monitoring tools (e.g., MLflow, Azure ML, SageMaker, Databricks, Python etc). Excellent stakeholder management and communication skills. Technical background in AI/ML, data science, or software engineering Experience with cloud-native AI environments More ❯

FEQ426R107 (EMC (energy, manufacturing and comms)) Location: London, UK Recruiter: Dina Hussain Industry Sectors we have roles in: Financial Services - Insurance or Banking Retail/CPG EMC (energy, manufacturing and comms) Public Sector Across all vertical sectors At Databricks, our More ❯

As a Big Data Solutions Architect (Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium-term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering More ❯

Cloudbeds is the leading platform redefining the concept of PMS for the hospitality industry, serving tens of thousands of properties in more than 150 countries worldwide. Built from the ground up to be masterfully unified and scalable, the award-winning More ❯

As a Big Data Solutions Architect (Resident Solutions Architect) on our Professional Services team for the Emerging Enterprise & Digital Natives business in EMEA , you will engage with customers on short- to medium-term projects, helping them navigate their big data More ❯

Join to apply for the Big Data Solutions Architect role at Databricks 6 days ago Be among the first 25 applicants Join to apply for the Big Data Solutions Architect role at Databricks Get AI-powered advice on this job More ❯

Job Description Senior Data Scientist Location: Manchester, UK Industry: Retail About the Role: Our leading retail client in the UK is seeking a highly skilled Senior Data Scientist to join their dynamic analytics team in Manchester. In this role, you More ❯