18 of 18 MLflow Jobs in the City of London

workflows. ML Ops & deployment: Familiarity with deploying models into production using APIs or microservices, and applying ML Ops practices such as experiment tracking (e.g., MLflow, Weights & Biases), model versioning, and performance monitoring. Experience collaborating with engineering teams to ensure scalable and maintainable deployment. Backend & service development: Experience building production-grade ...

Solid understanding of supervised/unsupervised learning, deep learning, and model evaluation techniques. Cloud & MLOps: Experience with AWS, GCP, or Azure; Docker/Kubernetes; MLflow or similar tools. Data Handling: Familiarity with big data frameworks (Spark, Hadoop) and data versioning tools (DVC). Soft Skills: Strong problem-solving, communication ...

data quality for machine learning applications. Machine Learning Operations (MLOps) - Experience deploying ML models to production environments using containerisation (Docker), orchestration (Kubernetes), model versioning (MLflow, DVC), monitoring model performance and drift, A/B testing frameworks, and implementing CI/CD pipelines for automated model training and deployment. Understanding ...

Python (pandas, NumPy, scikit-learn; PyTorch/TF a plus). Feature engineering, data quality validation, model training and optimisation. MLOps: experiment tracking (eg, MLflow), model registry, CI/CD for ML. Serving and orchestration: AWS SageMaker, EKS, batch & Real Time inference. Data pipelines: Spark/SQL, orchestration (Airflow), monitoring ...

deep learning techniques (e.g., TF-IDF, word embeddings, CNNs, RNNs). Familiarity with generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, or Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large, complex organisations or regulated industries. Strong working ...

algorithms. Consulting Experience: Proven track record of delivering solutions in a client-facing consulting environment. MLOps Expertise: Hands-on experience with tools such as MLflow, Kubeflow, TensorFlow Serving, or similar. Cloud Platforms: Proficiency in multi-cloud environments (AWS, Azure, GCP). DevOps & Automation: Strong knowledge of CI/CD pipelines ...

teams and delivering enterprise-grade data solutions. Preferred Qualifications Databricks certifications (e.g., Databricks Certified Data Engineer Professional, Architect ). Experience building ML solutions using MLflow or integrating with cloud ML services. Experience in BFSI, Retail, Telecom, or Healthcare data environments. Experience with real-time data processing (Kafka, EventHub, Kinesis). ...

statistical evaluation. Proven track record transitioning models from experimentation to production with governance and quality controls. Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, DVC). Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures. Familiarity with LLMOps tooling (LangSmith, LangChain, LangGraph). Understanding ...

experience with core GenAI frameworks (e.g., LangChain, LlamaIndex) and Agentic AI frameworks (e.g., AutoGen, CrewAI, LangGraph). Proficiency in MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Strong working knowledge and practical deployment experience on major cloud platforms (AWS, Azure, GCP), including their AI/ML services. Strong foundation ...

lifecycle management Lead documentation, knowledge transfer, and mentoring to upskill internal teams Technical requirements Strong Python and ML frameworks (PyTorch, TensorFlow) MLOps tooling (MLflow, Kubeflow or similar) Docker, Kubernetes, CI/CD pipelines Cloud platforms (AWS, Azure or GCP); Terraform experience preferred Financial services experience highly desirable A hands ...

Tools: Airflow, dbt, Databricks, Snowflake Developer Tooling & CI/CD: GitHub, Azure DevOps, Terraform (or other Infrastructure-as-Code tools) MLOps/LLMOps Frameworks: MLflow, AzureML, LangSmith ...

users. Strong proficiency in containerisation (Docker, Kubernetes) and orchestration of multi-stage ML workflows. Hands-on experience with ML platforms and tools such as MLflow, Kubeflow, Vertex AI, SageMaker, or similar model management systems. Practical knowledge of infrastructure as code, CI/CD best practices, and cloud platforms ...

similar distributed compute frameworks. Experience managing cloud infrastructure, Kubernetes, and CI/CD pipelines. Familiar with dataset versioning, orchestration, and experiment tracking (DVC, MLflow, Airflow). Ideally, we are looking for someone with prior experience working at an early-stage start-up. ...

pipelines for analytics and modelling workflows. Model development & deployment: Familiarity with deploying models into production environments, collaborating with engineering teams, and using tools like MLflow or Weights & Biases for experiment tracking and reproducibility. Proof of work in cloud environments, especially MS Azure, is a plus. Research mindset with business impact ...

sponsorship cannot be provided. Desirable: Knowledge of AWS services (e.g., Lambda, ECS, Bedrock, S3, SageMaker). Experience with ML engineering and MLOps (e.g., Docker, MLflow). Experience in regulated industries or government-related projects. Applying LLMs or advanced AI methods to real-world problems. Benefits: Competitive salary ...

Code skills. Experience designing and delivering modern IT/cloud architectures. Knowledge of modern data/ML platforms (e.g., Databricks, Azure ML, Synapse, MLflow, Airflow). Desirable Disaster recovery and cloud security best practices. Experience in research, life sciences, or health data environments. Data sharing agreements and DPIAs. Snowflake experience. ...

similar). Strong Python skills (Pandas, NumPy). Experience or exposure to NLP, transformers, and LLMs. Familiarity with ML tools like Weights & Biases or MLflow is a plus. Curious, proactive, and confident working independently. Ideally based near London for occasional client visits. 📩 Interested? Message me here or email mmatysik ...

develop backend systems (Python, FastAPI, Flask, NodeJS) Design and implement RAG pipelines (LangChain, Qdrant, embeddings) Build ETL & CI/CD workflows (Airflow, dbt, MLFlow) Integrate AI/LLM components into backend services Ensure reliability, scalability, and maintainability across systems Collaborate with a small, elite team of engineers and AI researchers … experience (Python, distributed systems, async APIs) Proven experience integrating AI or LLM systems (LangChain, vector DBs, etc.) Hands-on with some of Airflow, dbt, MLFlow, ETL, and CI/CD workflows Experience in early-stage startup environments — self-starter mindset Excited by ambiguity, ownership, and building from zero ...