1 to 25 of 34 MLflow Jobs in England

APIs. Deep understanding of AI/ML to enhance pipeline efficiency, with experience in TensorFlow, PyTorch, AutoML, Python/R, and MLOps platforms like MLflow and Kubeflow. Solid background in DevOps , including CI/CD automation with Bitbucket Pipelines, Azure DevOps, and GitHub. Capability to automate the deployment of data more »

machine learning systems. Expert in Python. Knowledge of common ML libraries like Pandas, NumPy and Scikit-Learn. Experience with ML workflow orchestration tools (Kubeflow, MLFlow, Airflow etc). Experience with Vertex AI Understanding of CI/CD pipelines and DevOps processes. Ability to collaborate with data scientists and software engineers. more »

Extra Kudos if you have Previous role as an MLOps engineer Use of ML frameworks e.g. pytorch, tensorflow Familiarity with MLOps platforms e.g. Kubeflow, MLFlow, Tensorflow Extended, ClearML, VertexAI, Amazon SageMaker Experience deploying ML models in production environments Benefits We provide: Competitive salary, benchmarked against the market and reviewed annually more »

Data Warehouse platforms and migration experience from legacy to Databricks.Relevant experience in designing and delivery Databricks based solutions i.e. Databricks Lakehouse, data science workflows (MLFlow, MLOps on Databricks), governance (Unity Catalogue), security and access design on Cloud technologies (AWS, GCP, Azure).Experience with design and implementation in big data technologies more »

Data Warehouse platforms and migration experience from legacy to Databricks.Relevant experience in designing and delivery Databricks based solutions i.e. Databricks Lakehouse, data science workflows (MLFlow, MLOps on Databricks), governance (Unity Catalogue), security and access design on Cloud technologies (AWS, GCP, Azure).Experience with design and implementation in big data technologies more »

data engineering to ML operations (training, serving, monitoring), and microservice/web application engineering.Our tech stack: Azure Data Lake, Azure Databricks (Notebooks, APIs, Workflows), MLflow, dbt, Harness CI/CD, OpenShift, Docker, GitHub, JIRADISCOVER your opportunity What will your essential responsibilities include?· Set engineering standards and be accountable for their 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 »

and analysis . Expertise in Python , along with familiarity with essential ML tools and libraries. Experience with ML experiment tracking and collaboration tools like MLflow and Weights & Biases . A strong foundation in software engineering, DevOps practices, MLOps deployment, and infrastructure management. An affinity for generative AI frameworks and SDKs more »

experience (Docker, Kubernetes, etc.) Good understanding of software best practises MongoDB (or NoSQL) experience Terraform experience Previous experience in managing the ML lifecycle with MLFlow Unfortunately sponsorship isn't provided for this role If you are interested please apply here or reach out to morgan.beck@xcede.com more »

Models. (Regression, Tree based, Unsupervised, NLP, open-source models). Experience with other Azure cloud services like Azure ML studio, Azure functions, Azure Pipelines, Mlflow, Promptflow, Azure OpenAI, Azure Synapse Analytics, etc., is a plus. Knowledge Graphs and LLM’s is advantageous. Machine learning algorithms and frameworks (e.g., TensorFlow, Keras more »

as Python or R, and extensive experience with ML algorithms and models. Experience with cloud services like Azure ML studio, Azure functions, Azure Pipelines, Mlflow, Azure Synapse Analytics, etc., is a plus. Solid understanding of statistical analysis, hypothesis testing, and experimental design. Expertise in machine learning algorithms and frameworks. Strong more »

Natural Language Processing and Computer Vision Strong grasp of basic probability concepts and machine learning lifecycle Experience with workflow and pipelining frameworks (e.g., Kubeflow, MLFlow, Argo) Understanding and application of Ethical AI considerations TO BE CONSIDERED…. Please either apply by clicking online or emailing me directly at . For 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 »

Models. (Regression, Tree based, Unsupervised, NLP, open-source models). Experience with other Azure cloud services like Azure ML studio, Azure functions, Azure Pipelines, Mlflow, Promptflow, Azure OpenAI, Azure Synapse Analytics, etc., is a plus. Understanding of Knowledge Graphs and LLM's is advantageous. Solid understanding of statistical analysis, hypothesis more »

TDD & CI/CD experience Containerisation experience (Docker, Kubernetes, etc.) MongoDB (or NoSQL) experience Terraform experience Previous experience in managing the ML lifecycle with MLFlow more »

TDD & CI/CD experience Containerisation experience (Docker, Kubernetes, etc.) MongoDB (or NoSQL) experience Terraform experience Previous experience in managing the ML lifecycle with MLFlow 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 »

Unix, and pytest. You're familiar with popular Python data mining and wrangling libraries, including pandas, numpy, sklearn, pytorch, langchain, llamaindex, bedrock, sagemaker, huggingface, mlflow, gradio, Flask, FastAPI, SQLAlchemy, psycopg2, boto3, gunicorn, pytest, and scrapy Experience with cloud services like Microsoft Azure (Data Factory, ML Studio, Synapse Analytics, etc.) Interest more »

DevOps, CI/CD pipelines, GitHub, and Kubernetes (AKS) for efficient software development and deployment. Implement ML/OPS solutions using Azure ML, Databricks MLFlow, and LLMOps for streamlined Machine Learning operations. Ensure data governance and data cataloging standards are maintained, utilizing tools such as Collibra and Talend Data Catalogue. … AI. Knowledge of Azure DevOps, CI/CD pipelines, GitHub, Kubernetes (AKS). Experience with ML/OPS tools such as Azure ML, Databricks MLFlow, LLMOps. Familiarity with data governance, data cataloging tools (Collibra, Talend Data Catalogue). Experience with visualization and reporting tools like Power BI, Tableau, and front 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 »

Teams to drive innovation and excellence About you Ability to Design and implement MLOps pipelines on AWS Experience with MLOps Frameworks, mainly SageMaker and MLFlow Strong programming experience in production environments (Python) Strong infrastructure knowledge (Terraform) Experience with DevOps tools (Docker, Kubernetes) Experience with integrating with data warehouses (Snowflake) and more »

Atlassian Bamboo). 🔹 Ambition to shape our ML-based services and enhance efficiency. 🔹 Good communication skills in English. 🔹 Experience with model management tools (e.g., mlflow) and MLOps. Nice-to-Haves: 🔹 Experience with Kafka and Vector Databases. 🔹 Experience in deploying large language models (LLMs) at scale. If you are interested in more »