1 to 14 of 14 MLflow Jobs with Hybrid or WFH Options

Spark, geospatial data/modelling and insurance are a plus. Exposure to MLOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc are desirable We’ll help you gain Experience working in a high-performance environment where collaboration and business impact are BAU. Experience more »

Vision applications. • Strong understanding of basic probability concepts. • In-depth knowledge of the machine learning lifecycle and collaboration facilitation. • Workflow/pipelining frameworks (Kubeflow, MLFlow, Argo or equivalents). • Understanding and application of key considerations for Ethical AI. Benefits : • Base Salary: £45,000 - £75,000 (DoE) • Discretionary Bonus: Circa more »

Vision applications. • Strong understanding of basic probability concepts. • In-depth knowledge of the machine learning lifecycle and collaboration facilitation. • Workflow/pipelining frameworks (Kubeflow, MLFlow, Argo or equivalents). • Understanding and application of key considerations for Ethical AI. Benefits : • Base Salary: £45,000 - £75,000 (DoE) • Discretionary Bonus: Circa more »

Vision applications. Strong understanding of basic probability concepts. In-depth knowledge of the machine learning lifecycle and collaboration facilitation. Workflow/pipelining frameworks (Kubeflow, MLFlow, Argo or equivalents). Understanding and application of key considerations for Ethical AI. Benefits: Base Salary: £45,000 - £75,000 (DoE) Discretionary Bonus: Circa more »

Vision applications. • Strong understanding of basic probability concepts. • In-depth knowledge of the machine learning lifecycle and collaboration facilitation. • Workflow/pipelining frameworks (Kubeflow, MLFlow, Argo or equivalents). • Understanding and application of key considerations for Ethical AI. Benefits: • Base Salary: £60,000 - £85,000 (DoE) • Discretionary Bonus: Circa more »

practices sch as CI/CD. Experience deploying/monitoring machine learning models and following best practices. The Ability to develop pipelines using SageMaker, MLFlow or similar frameworks. Strong experience with data programming frameworks such as Apache Spark. Understanding of common Data Science and Machine Learning models, libraries and frameworks. more »

Solid knowledge of Data Governance, Data Catalog, and Master Data Management. Understanding of Advanced Analytics and Model Management, encompassing Azure Databricks, Azure ML/MLFlow, and deployment of models using Azure Kubernetes Service. Excellent oral and written communication skills. Please apply if of interest. more »

Management. (You will be skilled up in this sought after area) Understanding of Advanced Analytics and Model Management, encompassing Azure Databricks, Azure ML/MLFlow, and deployment of models using Azure Kubernetes Service. Excellent oral and written communication skills. Please apply if of interest. more »

Management. (You will be skilled up in this sought after area) Understanding of Advanced Analytics and Model Management, encompassing Azure Databricks, Azure ML/MLFlow, and deployment of models using Azure Kubernetes Service. Excellent oral and written communication skills. Please apply if of interest more »

/CD best practices to increase the efficiency in deployment and management of resources. Experience with building and or using model management tools (e.g. mlflow)& MLOps (model orchestration, updating, etc.) Additional Information Our commitment Equal opportunities are important to us. We believe that diversity and inclusion at The Stepstone Group more »

We are currently recruiting for one of our trusted clients who are look for a Data Engineer. Join our client, a leading player in the pet health services and insurance industry, as they aim to secure the coveted position of more »

Role: As a Machine Learning Engineer: Apply Machine Learning Engineering project You will build the Machine Learning Infrastructures interacting with CI/CD pipelines, MLFlow, Kafka, and Kubernetes. You will be developing and Deploying Advanced Analytical algorithms/scalable solutions using Cloud. You will be working with a team of … implementation of Machine Learning and clustering techniques with commercial experience as a Data Scientist. DevOps experience in CI/CD. Experience using Tensorflow, Kubernetes, MLFlow, Kafka, and Airflow. Experience using Python is a must (tools like AWS and Spark are beneficial) Excellent communication skills and team and colleague engagement. A more »

Role: As a Machine Learning Engineer: Apply Machine Learning Engineering project You will build the Machine Learning Infrastructures interacting with CI/CD pipelines, MLFlow, Kafka, and Kubernetes. Lead a Team of ML Engineers. You will be developing and Deploying Advanced Analytical algorithms/scalable solutions using Cloud. You will … implementation of Machine Learning and clustering techniques with commercial experience as a Data Scientist. DevOps experience in CI/CD. Experience using Tensorflow, Kubernetes, MLFlow, Kafka, and Airflow. Experience using Python is a must (tools like AWS and Spark are beneficial) Excellent communication skills and team and colleague engagement. A more »