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9 of 9 Permanent MLflow Jobs in Central London
City of London, London, United Kingdom Hybrid / WFH Options Explore Group
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 ❯
london (city of london), south east england, united kingdom Hybrid / WFH Options Explore Group
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 ❯
City of London, London, United Kingdom Hybrid / WFH Options KPMG UK
Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. Proven experience with modern engineering practices Git, version control, unit testing and containerisation. Familiarity with agile work methodologies and tools like Jira and Confluence. Behavioural Attributes and Skills More ❯
london (city of london), south east england, united kingdom Hybrid / WFH Options KPMG UK
Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. Proven experience with modern engineering practices Git, version control, unit testing and containerisation. Familiarity with agile work methodologies and tools like Jira and Confluence. Behavioural Attributes and Skills More ❯
City of London, London, United Kingdom Hybrid / WFH Options Experis UK
of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. More ❯
london (city of london), south east england, united kingdom Hybrid / WFH Options Experis UK
of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. More ❯
City of London, London, United Kingdom Omnis Partners
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 ❯
City of London, London, United Kingdom Harnham
analytics, or data science. Hands-on familiarity with modern data stacks – SQL, dbt, Airflow, Snowflake, Looker/Power BI. Understanding of the AI/ML lifecycle – including tooling (Python, MLflow) and best-practice MLOps. Comfortable working across finance, risk, and commercial functions. Experience operating in a regulated environment, ideally with exposure to dual regulation and resilience frameworks. Please note - this More ❯
City of London, London, United Kingdom Hybrid / WFH Options Jendi
Pinecone, Weaviate, FAISS). Work with structured/unstructured data to build pipelines (SQL, Spark, Databricks, Kafka/Kinesis) and feature stores. Deploy and scale with MLOps best practice ( MLflow, W&B, Kubeflow, Docker/Kubernetes, CI/CD). Optimise performance, latency, and cost trade-offs across Azure, AWS, or GCP AI stacks . Collaborate directly with our world … Business and custom GPT development , including enterprise integration and compliance guardrails. Proven engineering skills — Python (PyTorch/TensorFlow, JAX) , SQL/Spark, data wrangling, API integration. MLOps & deployment experience — MLflow, W&B, Docker/Kubernetes, CI/CD pipelines. Track record shipping real-world AI systems with measurable outcomes, not just prototypes. Tier-one background preferred — IIT/IISc/ More ❯
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Salary Guide MLflow Central London - 25th Percentile
- £97,500
- Median
- £105,000
- 75th Percentile
- £112,500
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