9 of 9 Permanent MLflow Jobs in the City of London

related B2C environments Strong programming skills in Python, with experience using libraries like scikit-learn, XGBoost, and pandas Practical experience in MLOps or strong knowledge of model deployment (e.g. MLflow, Airflow, Docker, Kubernetes, model monitoring tools) Familiarity with cloud environments (AWS, GCP, or Azure) and data pipelines Excellent communication skills—able to explain technical work to non-technical stakeholders and More ❯

Skills: Experience using R and NLP or 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, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations or regulated industries. Strong working knowledge of Excel 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 ❯

mentoring and managing data science teams. Deep knowledge of media measurement techniques, such as media mix modelling. Experience with advanced AI techniques, including NLP, GenAI, and CausalAI. Familiarity with MLFlow, API design (FastAPI), and dashboard building (Dash). If this role looks of interest, reach out to Joseph Gregory 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 ❯

with Databricks or similar platforms Proven track record in predictive modelling with messy, real-world datasets (survey, geospatial, or similar) Hands-on experience with MLOps tools and practices (e.g., MLFlow) and deploying models in cloud environments (GCP, AWS, or Azure) Proactive, creative problem solver with a startup mindset and strong communication skills Comfortable taking technical ownership and leading ML projects More ❯

including APIs, data structures, and async processing * Databricks/Microsoft Fabric * Cloud, preferably Azure (Data Lake, Functions, App Services) * Containerisation with Docker and CI/CD pipelines * MLOps tooling (MLFlow, Git-based versioning, environment tracking) Desirable Skills & Interests * LangChain, Langflow, or similar frameworks for building AI agents * LLMs or intelligent automation workflows * High-availability, scalable systems (microservices, event- based architectures More ❯

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 ❯

solutions using cutting-edge tools like LangGraph, FastAPI, and HuggingFace. Own the full AI product lifecycle - from idea to production. Architect intelligent systems using Python, microservices, and MLOps tooling (MLflow, DVC). Work closely with cross-functional teams to turn real-world problems into working software. 🛠️ What You Bring: Fluency in Python and strong grasp of ML/DL concepts. More ❯