1 to 25 of 34 DemandTrendPermanent MLflow Jobs in England

with a focus on practical application and performance trade-offs. Experience with cloud platforms (e.g., AWS, Azure) and containerisation (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, SageMaker, Airflow). Experience working with large-scale datasets and distributed computing frameworks (e.g., Spark). Strong communication skills and ability to work collaboratively in a team environment. MSc or More ❯

with a focus on practical application and performance trade-offs. Experience with cloud platforms (e.g., AWS, Azure) and containerisation (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, SageMaker, Airflow). Experience working with large-scale datasets and distributed computing frameworks (e.g., Spark). Strong communication skills and ability to work collaboratively in a team environment. MSc or More ❯

with a focus on practical application and performance trade-offs. Experience with cloud platforms (e.g., AWS, Azure) and containerisation (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, SageMaker, Airflow). Experience working with large-scale datasets and distributed computing frameworks (e.g., Spark). Strong communication skills and ability to work collaboratively in a team environment. MSc or More ❯

in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar). Experience working with cloud platforms (AWS, Azure, or GCP). Solid understanding of CNNs, object detection, segmentation, and image classification. Strong problem-solving skills More ❯

in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar). Experience working with cloud platforms (AWS, Azure, or GCP). Solid understanding of CNNs, object detection, segmentation, and image classification. Strong problem-solving skills More ❯

in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar). Experience working with cloud platforms (AWS, Azure, or GCP). Solid understanding of CNNs, object detection, segmentation, and image classification. Strong problem-solving skills More ❯

in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar). Experience working with cloud platforms (AWS, Azure, or GCP). Solid understanding of CNNs, object detection, segmentation, and image classification. Strong problem-solving skills More ❯

in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar). Experience working with cloud platforms (AWS, Azure, or GCP). Solid understanding of CNNs, object detection, segmentation, and image classification. Strong problem-solving skills More ❯

Experience with Google Cloud Platform and/or Azure Cloud Services (DataFactory, Functions, SSIS) Hands-on experience with Databricks (GCP or Azure) Experience deploying and maintaining ML models (e.g., MLflow, Vertex AI, Azure ML) Beneficial Experience with Spark and other distributed data processing frameworks Exposure to MLOps tooling for orchestration, CI/CD, and monitoring Experience with Elasticsearch or similar More ❯

the following technologies : Azure, AWS, GCP Airflow, dbt, Databricks, Snowflake, etc. GitHub, Azure DevOps and related developer tooling and CI/CD platforms, Terraform or other Infra-as-Code MLflow, AzureML or similar for MLOps; LangSmith, Langfuse and similar for LLMOps The difference to our "AI Engineer" role is: Do you "use/consume" these technologies, or are you the More ❯

performance Work in a fast-paced start-up culture where your ideas and input matter Skills Strong background in Python and software engineering principles Hands-on with MLOps tools (MLflow, Kubeflow, SageMaker, or similar) Experience with CI/CD (Jenkins, GitLab, Argo, or similar) Familiarity with cloud platforms (AWS, GCP, or Azure) Solid understanding of Docker, Kubernetes, Terraform is a More ❯

performance Work in a fast-paced start-up culture where your ideas and input matter Skills Strong background in Python and software engineering principles Hands-on with MLOps tools (MLflow, Kubeflow, SageMaker, or similar) Experience with CI/CD (Jenkins, GitLab, Argo, or similar) Familiarity with cloud platforms (AWS, GCP, or Azure) Solid understanding of Docker, Kubernetes, Terraform is a More ❯

performance Work in a fast-paced start-up culture where your ideas and input matter Skills Strong background in Python and software engineering principles Hands-on with MLOps tools (MLflow, Kubeflow, SageMaker, or similar) Experience with CI/CD (Jenkins, GitLab, Argo, or similar) Familiarity with cloud platforms (AWS, GCP, or Azure) Solid understanding of Docker, Kubernetes, Terraform is a More ❯

foundational LLMs to custom built cognitive agents, solving real world business challenges. Establishing scalable ML/AI pipelines and infrastructure, working closely with data engineering and DevOps functions (Kubernetes, MLflow, Vertex AI, etc.). Acting as a thought leader, identifying new AI use cases and communicating technical vision to executive stakeholders and cross-functional teams. Champion ethical AI principles, ensuring More ❯

CD and automation: Jenkins, GitLab, Sonatype Nexus, Terraform, Ansible, Argo CD Experience with cloud platforms: AWS (primary), with GCP/Azure exposure Experience with MLOps/data tooling: DVC, MLFlow, Airflow, Dagster, CVAT, Weights & Biases; data lakes/warehouses What we can offer you: Up to 65k p.a. depending on experience and location Flexible working Inclusive and relaxed company culture More ❯

record delivering production-grade ML models Solid grasp of MLOps best practices Confident speaking to technical and non-technical stakeholders 🛠️ Tech you’ll be using: Python, SQL, Spark, R MLflow, vector databases GitHub/GitLab/Azure DevOps Jira, Confluence 🎓 Bonus points for: MSc/PhD in ML or AI Databricks ML Engineer (Professional) certified More ❯

record delivering production-grade ML models Solid grasp of MLOps best practices Confident speaking to technical and non-technical stakeholders 🛠️ Tech you’ll be using: Python, SQL, Spark, R MLflow, vector databases GitHub/GitLab/Azure DevOps Jira, Confluence 🎓 Bonus points for: MSc/PhD in ML or AI Databricks ML Engineer (Professional) certified More ❯

Frameworks: PyTorch, TensorFlow, Hugging Face Transformers Bio-AI Tools: AlphaFold, RoseTTAFold, BioBERT, DeepCell, Cellpose Data Sources: Genomic datasets, microscopy images, biomedical literature Cloud & DevOps: AWS/GCP, Docker, Kubernetes, MLflow Languages: Python (essential), SQL, Bash Ideal Candidate Profile: 4+ years of experience in machine learning, with at least 2 years in biotech, healthcare, or life sciences Strong understanding of biological More ❯

solutions. This is a strategic team build working closely with Databricks professional services on marquee client engagements. 🛠️ Databricks-Focused Tech Stack: Databricks (Primary platform - all roles) Databricks ML/MLflow AWS/Azure/GCP (Databricks deployment) Python & SQL (Databricks native) Delta Lake & Unity Catalog 💰 Package: Salary: £70k-£110k (negotiable) Performance bonus Professional certifications funded 20 dedicated development days Flexible More ❯

solutions. This is a strategic team build working closely with Databricks professional services on marquee client engagements. 🛠️ Databricks-Focused Tech Stack: Databricks (Primary platform - all roles) Databricks ML/MLflow AWS/Azure/GCP (Databricks deployment) Python & SQL (Databricks native) Delta Lake & Unity Catalog 💰 Package: Salary: £70k-£110k (negotiable) Performance bonus Professional certifications funded 20 dedicated development days Flexible More ❯

solutions. This is a strategic team build working closely with Databricks professional services on marquee client engagements. 🛠️ Databricks-Focused Tech Stack: Databricks (Primary platform - all roles) Databricks ML/MLflow AWS/Azure/GCP (Databricks deployment) Python & SQL (Databricks native) Delta Lake & Unity Catalog 💰 Package: Salary: £70k-£110k (negotiable) Performance bonus Professional certifications funded 20 dedicated development days Flexible More ❯

solutions. This is a strategic team build working closely with Databricks professional services on marquee client engagements. 🛠️ Databricks-Focused Tech Stack: Databricks (Primary platform - all roles) Databricks ML/MLflow AWS/Azure/GCP (Databricks deployment) Python & SQL (Databricks native) Delta Lake & Unity Catalog 💰 Package: Salary: £70k-£110k (negotiable) Performance bonus Professional certifications funded 20 dedicated development days Flexible More ❯

solutions. This is a strategic team build working closely with Databricks professional services on marquee client engagements. 🛠️ Databricks-Focused Tech Stack: Databricks (Primary platform - all roles) Databricks ML/MLflow AWS/Azure/GCP (Databricks deployment) Python & SQL (Databricks native) Delta Lake & Unity Catalog 💰 Package: Salary: £70k-£110k (negotiable) Performance bonus Professional certifications funded 20 dedicated development days Flexible More ❯

Python and scripting for automation Solid understanding of cloud networking, security, and cross-cloud connectivity Experience in monitoring, observability, and cost optimisation Nice to Have Experience with ML tooling (MLflow, Kubeflow) Knowledge of FastAPI , Databricks, or Snowflake Exposure to SRE practices or cloud security certifications Familiarity with Prometheus , Grafana , or Datadog Interested? If you want to be part of a More ❯

in cloud environments, with an emphasis on scalability, code clarity, and long-term maintainability Hands-on experience with Databricks and/or Spark, especially Delta Lake, Unity Catalog, and MLflow Deep familiarity with cloud platforms, particularly AWS and Google Cloud Proven ability to manage data architecture and production pipelines in a fast-paced environment Track record of leading or independently More ❯