14 of 14 MLflow Jobs in the South East

Experience deploying ML models or managing AI/ML workflows in production. Working knowledge of big data technologies like Spark , Hive , or Hadoop . Familiarity with MLOps tools (e.g., MLflow , Kubeflow , DataRobot ). Education Bachelor’s degree in Computer Science , Software Engineering , or a related technical field — or equivalent practical experience. Why Join Us Work on cutting-edge technologies and More ❯

with marketing strategists, data analysts, data engineers, and product owners to define use cases and deliver scalable solutions. Model Deployment & Monitoring: Deploy models using MLOps practices and tools (e.g., MLflow, Airflow, Docker, cloud platforms) ensuring performance, reliability, and governance compliance. Innovation & Research: Stay current on advancements in AI/ML and proactively bring forward new ideas, frameworks, and techniques that … results for non-technical stakeholders. Strong proficiency in Python, SQL, and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch). Experience with model operationalization using tools like Docker, Kubernetes, MLflow, or SageMaker. Marketing KPIs knowledge: CTR, conversion rate, MQL to SQL, ROI, CLV, CAC, retention. Experience working with multi-channel marketing data: CRM (e.g., Salesforce), email, web analytics, social media More ❯

Who We Are For years, artists have been 'shooting in the dark' when it comes to their marketing. There's a clear lack of robust, transparent and accessible marketing tools for musicians and artists to use to promote their music. More ❯

Excellent communication skills and a passion for mentoring and team leadership. Nice to Have Experience with data engineering tools (Airflow, Kafka, Spark). Knowledge of MLOps practices and tools (MLflow, Kubeflow). Contributions to open-source projects or AI research. Why Join? Work on impactful AI products used by global clients. Competitive salary, stock options, and flexible working hours. A More ❯

Strong understanding of SQL, NoSQL, and data modeling. Familiarity with cloud platforms (AWS, Azure, GCP) for deploying ML and data solutions. Knowledge of MLOps practices and tools, such as MLflow or Kubeflow. Strong problem-solving skills, with the ability to troubleshoot both ML models and data systems. A collaborative mindset and ability to work in a fast-paced, small team More ❯

as TensorFlow, PyTorch, Scikit-learn, and Keras. Understanding of algorithms and techniques for supervised and unsupervised learning. Experience with tools for model monitoring, logging, and performance evaluation, such as MLflow or Prometheus. Strong scripting skills in Bash, PowerShell, or similar scripting languages for automation of tasks and ability to write reusable and maintainable code to streamline ML operations Proficient in 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 ❯

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 ❯

based with the right to work and able to be in the office 2–3 days per week Nice to Have Background in healthcare, clinical tech, or MLOps tooling (MLflow, Kubeflow, Vertex Pipelines) What’s on Offer Competitive salary + meaningful equity ‍♂️ 25 days holiday + UK bank holidays Flexible hours and a sustainable work pace Bright, collaborative office minutes More ❯

and platform engineering teams to identify technical gaps, scope backend development efforts, and deliver core platform capabilities such as: Model training orchestration CI/CD for ML (e.g., using MLflow, Kubeflow, or Vertex AI Pipelines) Model versioning, monitoring, and governance Enable high-impact AdTech use cases including: Marketing Mix Modeling (MMM) Real-time personalization and bidding Audience segmentation and targeting More ❯

startup environments UK-based and available to work 2–3 days per week in-office (London) Bonus Points Experience in healthcare, medtech, or clinical systems Familiarity with MLOps tooling (MLflow, Kubeflow, Vertex Pipelines More ❯

FastAPI, or other common web frameworks. An understanding of core concepts in ML, data science and MLOps. Nice-to-Have : Built agentic workflows/LLM tool-use. Experience with MLFlow, WandB, LangFuse, or other MLOps tools. Experience with AirFlow, Spark, Kafka or similar. Why Plexe? Hard problems: we're automating the entire ML/AI lifecycle from data engineering to More ❯

occasions. To be a successful, the ideal Machine Learning Engineer candidate will have: · Highly skilled in Python. · Knowledge of AWS or GCP. · Ideally experience of SKLearn/Docker/MLFlow or PyTest · Excellent communication and problem solving skills. What is in it for you? As a talented Machine Learning Engineer you can expect: · Great salary - Up to £80,000 base More ❯

work collaboratively across disciplines. ● Experience integrating or leveraging Large Language Models (LLMs) via APIs or platform services (e.g., OpenAI, Anthropic, Cohere). ● Familiarity with MLOps tools and practices (e.g., MLflow, SageMaker, Kubeflow). ● Experience in startup or fast-paced environments with rapidly evolving requirements Personal qualities ● Ambitious ● Driven ● Ability to work as part of a collaborative team but also work More ❯