176 to 200 of 348 MLflow Jobs in the UK

containerization, and cloud deployment for large-scale models. Solid programming skills in Python and familiarity with machine learning frameworks like TensorFlow, PyTorch, Hugging Face Transformers, and MLOps tools (e.g., MLflow, Kubeflow). Strong analytical and problem-solving skills, with an aptitude for translating complex theoretical research into practical applications. Day to Day Conduct research and implementation on the development, training More ❯

containerization, and cloud deployment for large-scale models. Solid programming skills in Python and familiarity with machine learning frameworks like TensorFlow, PyTorch, Hugging Face Transformers, and MLOps tools (e.g., MLflow, Kubeflow). Strong analytical and problem-solving skills, with an aptitude for translating complex theoretical research into practical applications. Day to Day Conduct research and implementation on the development, training More ❯

to non-technical stakeholders. Expertise in identifying and mitigating bias in AI/ML models. Proficiency in Python and familiarity with tools/platforms like Azure, AWS, GCP, Databricks, MLFlow, Airflow, Plotly Dash, and Streamlit. Our Benefits Include Group pension plan, life assurance, income protection, and critical illness cover. Private medical and dental insurance. Cyclescheme, Techscheme, and season ticket loans. More ❯

data modeling, data warehousing, data integration, and data governance. Databricks Expertise: They have hands-on experience with the Databricks platform, including its various components such as Spark, Delta Lake, MLflow, and Databricks SQL. They are proficient in using Databricks for various data engineering and data science tasks. Cloud Platform Proficiency: They are familiar with cloud platforms like AWS, Azure, or More ❯

ingestion patterns, storage layers (Delta Lake), processing frameworks (Spark), and consumption mechanisms. Technology Selection: Evaluate and recommend optimal Databricks features and integrations (e.g., Unity Catalog, Photon, Delta Live Tables, MLflow) and complementary cloud services (e.g., Azure Data Factory, Azure Data Lake Storage, Power BI). Security & Governance Frameworks: Design robust data governance, security, and access control models within the Databricks More ❯

ingestion patterns, storage layers (Delta Lake), processing frameworks (Spark), and consumption mechanisms. Technology Selection: Evaluate and recommend optimal Databricks features and integrations (e.g., Unity Catalog, Photon, Delta Live Tables, MLflow) and complementary cloud services (e.g., Azure Data Factory, Azure Data Lake Storage, Power BI). Security & Governance Frameworks: Design robust data governance, security, and access control models within the Databricks More ❯

ingestion patterns, storage layers (Delta Lake), processing frameworks (Spark), and consumption mechanisms. Technology Selection: Evaluate and recommend optimal Databricks features and integrations (e.g., Unity Catalog, Photon, Delta Live Tables, MLflow) and complementary cloud services (e.g., Azure Data Factory, Azure Data Lake Storage, Power BI). Security & Governance Frameworks: Design robust data governance, security, and access control models within the Databricks More ❯

work in‐office in Euston 2–3 days per week (right to work in the UK required). Nice‐to‐haves Clinical or health‐tech domain knowledge. MLOps tooling (MLflow, Kubeflow, Vertex Pipelines). Benefits Competitive salary and attractive equity in a high growth startup 25 days holiday + UK bank holidays. Flexible hours & focus on sustainable pace. Bright office More ❯

work in‐office in Euston 2–3 days per week (right to work in the UK required). Nice‐to‐haves Clinical or health‐tech domain knowledge. MLOps tooling (MLflow, Kubeflow, Vertex Pipelines). Benefits Competitive salary and attractive equity in a high growth startup 25 days holiday + UK bank holidays. Flexible hours & focus on sustainable pace. Bright office More ❯

tools. Exposure to real-time/streaming data (Kafka, Spark Streaming, etc.). Understanding of data mesh , data contracts , or domain-driven data architecture . Hands on experience with MLflow and Llama #J-18808-Ljbffr More ❯

and deploying LLM-powered applications in production. Familiarity with transformer architectures and practical handling of LLM context, prompt chaining, and prompt engineering. Hands-on experience with MLOps tools like MLflow, Weights & Biases, and orchestration platforms like Kubeflow or Databricks. Deep understanding of cloud platforms (especially Azure and AWS), containers, microservices, and event-driven architecture. Strong problem-solving and debugging skills More ❯

ingestion patterns, storage layers (Delta Lake), processing frameworks (Spark), and consumption mechanisms. Technology Selection: Evaluate and recommend optimal Databricks features and integrations (e.g., Unity Catalog, Photon, Delta Live Tables, MLflow) and complementary cloud services (e.g., Azure Data Factory, Azure Data Lake Storage, Power BI). Security & Governance Frameworks: Design robust data governance, security, and access control models within the Databricks More ❯

code (Docker, Terraform, etc) Build efficient data pipelines to handle text and audio data processing for ML models Deploy NLP models in cloud environments (AWS SageMaker) through Jenkins Use MLflow and other ML Ops applications to streamline ML workflows and adhere to data privacy and residency guidelines Communicate your work throughout the team and related departments Collaboration is a key More ❯

Refinitiv, prime brokerage APIs, and regulatory systems Advanced Security: Zero-trust architecture, FCA compliance, and financial-grade security protocols 🔧 Technical Stack You'll Lead AI/ML: TensorFlow, PyTorch, MLflow, NVIDIA Triton, custom financial LLMs Data: Kafka, Flink, Snowflake, ClickHouse, Neo4j, vector databases Backend: FastAPI, GraphQL, microservices, Docker, Kubernetes Frontend: React/Next.js, TypeScript, real-time dashboards, mobile apps Cloud More ❯

Refinitiv, prime brokerage APIs, and regulatory systems Advanced Security: Zero-trust architecture, FCA compliance, and financial-grade security protocols 🔧 Technical Stack You'll Lead AI/ML: TensorFlow, PyTorch, MLflow, NVIDIA Triton, custom financial LLMs Data: Kafka, Flink, Snowflake, ClickHouse, Neo4j, vector databases Backend: FastAPI, GraphQL, microservices, Docker, Kubernetes Frontend: React/Next.js, TypeScript, real-time dashboards, mobile apps Cloud More ❯

Refinitiv, prime brokerage APIs, and regulatory systems Advanced Security: Zero-trust architecture, FCA compliance, and financial-grade security protocols Technical Stack You'll Lead AI/ML: TensorFlow, PyTorch, MLflow, NVIDIA Triton, custom financial LLMs Data: Kafka, Flink, Snowflake, ClickHouse, Neo4j, vector databases Backend: FastAPI, GraphQL, microservices, Docker, Kubernetes Frontend: React/Next.js, TypeScript, real-time dashboards, mobile apps Cloud More ❯

globally distributed group tackling novel R & D problems that directly impact customers. OUR TECHNOLOGY STACK: Python • Agentic tools (Autogen, Semantic Kernel, LangChain) • SQL • MongoDB • Third-party LLM APIs • LiteLLM • MLflow • Google Cloud Platform • Docker • PyTorch • Hugging Face Transformers • SPARQL • Kubernetes WHAT YOU WILL BE DOING AT BEAMERY Join us at the forefront of transforming how organisations manage talent and plan More ❯

but not essential NLP/Deep learning experience (e.g. huggingface, spaCy) Deep learning framework experience (preferably PyTorch) MLOps experience (e.g. data and model versioning, model deployment CI/CD, MLFlow/DVC) Cloud platform experience, especially from an ML standpoint (AWS preferred) Statistical testing experience Experience with AWS Bedrock Experience with C# Containerization via Docker. Awareness of basic data science More ❯

complex property management workflows and decision-making processes Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch), LLM orchestration tools (LangChain, LangGraph), MLOps practices and tooling (such as MLflow, Kubeflow, or similar), vector databases, and cloud platforms (AWS, Azure, GCP) with their AI/ML offerings Preferably hands-on experience with voice technologies and computer vision for relevant property More ❯

but not essential NLP/Deep learning experience (e.g. huggingface, spaCy) Deep learning framework experience (preferably PyTorch) MLOps experience (e.g. data and model versioning, model deployment CI/CD, MLFlow/DVC) Some basic devops experience useful (kubectl, helm, etc.) Cloud platform experience, especially from an ML standpoint (AWS preferred) Statistical testing experience Basic AWS resource management, including microservice deployment. More ❯

Proven track record of leading complex AI projects in an agile environment Strong technical proficiency with modern ML tools and frameworks: PyTorch, TensorFlow, SparkMLLib, SciPy, Scikit-Learn, NLTK (etc) MLflow or similar ML lifecycle tools Cloud platforms (AWS/Azure/GCP) Experience with AI governance and responsible AI practices Understanding of public sector data requirements and compliance Outstanding communication More ❯

Proven track record of leading complex AI projects in an agile environment Strong technical proficiency with modern ML tools and frameworks: PyTorch, TensorFlow, SparkMLLib, SciPy, Scikit-Learn, NLTK (etc) MLflow or similar ML lifecycle tools Cloud platforms (AWS/Azure/GCP) Experience with AI governance and responsible AI practices Understanding of public sector data requirements and compliance Outstanding communication More ❯

Proven track record of leading complex AI projects in an agile environment Strong technical proficiency with modern ML tools and frameworks: PyTorch, TensorFlow, SparkMLLib, SciPy, Scikit-Learn, NLTK (etc) MLflow or similar ML lifecycle tools Cloud platforms (AWS/Azure/GCP) Experience with AI governance and responsible AI practices Understanding of public sector data requirements and compliance Outstanding communication More ❯

Proven track record of leading complex AI projects in an agile environment Strong technical proficiency with modern ML tools and frameworks: PyTorch, TensorFlow, SparkMLLib, SciPy, Scikit-Learn, NLTK (etc) MLflow or similar ML lifecycle tools Cloud platforms (AWS/Azure/GCP) Experience with AI governance and responsible AI practices Understanding of public sector data requirements and compliance Outstanding communication More ❯

data acquisition and deployment (mainly SharePoint). Desirable: Experience with Azure or other cloud services. Experience with dataset versioning tools (e.g. DVC) Experience with ML models versioning tools (e.g. MLFlow) Understanding of data structures, algorithms, OOP concepts. Understanding of basic software engineering design patterns. Interest in AEC or previous experience or research with the AEC industry. Personal Skills: Proactive in More ❯