24 of 24 MLflow Jobs in the South East

managed AI/ML services Practical experience with Docker, Kubernetes, and container orchestration Databricks expertise, including ML workflows and data pipeline integration Familiarity with MLflow, DVC, Prometheus, and Grafana for versioning and monitoring Bachelor's or Master's degree in Computer Science, Engineering, or related field (or equivalent experience) Fluency More ❯

C# or Java, cloud SDKs and APIs. AI/ML expertise for pipeline efficiency, familiar with TensorFlow, PyTorch, AutoML, Python/R, and MLOps (MLflow, Kubeflow). Solid in DevOps, CI/CD automation with Bitbucket Pipelines, Azure DevOps, GitHub. Automate deployment of data pipelines and applications using Bash, PowerShell More ❯

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 More ❯

cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Hands-on experience with CI/CD pipelines, version control, and ML workflows (MLflow, Kubeflow). Proven track record of delivering ML models that solve real-world business challenges at scale. Excellent communication skills with the ability to work More ❯

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 ❯

PostgreSQL Databricks Containerisation: Docker, Kubernetes CI/CD: Azure DevOps, GitHub Actions Relational databases and data lake architecture Model and data pipeline integration (e.g. MLflow) Microsoft Azure (Functions, Storage, Compute) Monitoring tools (Grafana, Prometheus, etc.) Mentoring and knowledge sharing within the team Senior Engineer - Desirable Skills: Experience in energy supply More ❯

version control, CI/CD pipelines, and test-driven development. Nice to Have: Experience within financial services or fintech. Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker). Understanding of regulatory or compliance frameworks. Academic background in mathematics, statistics, or quantitative disciplines. Who You Are: A natural problem-solver and More ❯

with CI/CD pipelines and infrastructure-as-code tools (Terraform is a plus). Experience with Airflow or similar orchestration tools. Familiarity with MLflow or MLOps practices. Knowledge of data warehousing solutions (Snowflake, Redshift, BigQuery). Consulting background is a plus. Strong communication skills (oral & written) Rights to work More ❯

proficiency in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or email me at mmatysik@trg-uk.com. More ❯

years leading Databricks-based solutions. Proven experience in a consulting environment delivering large-scale data platform projects. Hands-on expertise in Spark, Delta Lake, MLflow, Unity Catalog, and DBSQL. Strong proficiency in Python, SQL, and at least one major cloud platform (AWS, Azure, or GCP). Excellent communication skills and More ❯

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 ❯

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 ❯

/GCP. · Ability to manage cloud infrastructure to ensure high availability, scalability, and cost efficiency. Nice-to-Have · Experience with ML orchestration platforms like MLflow, SageMaker Pipelines, Kubeflow, or similar. · Familiarity with model quantization, pruning, or other performance optimization techniques. · Exposure to distributed training frameworks like Unsloth, DeepSpeed, Accelerate, or More ❯

/ML solutions in production environments Excellent communicator, comfortable working directly with clients and multidisciplinary teams Hands-on experience with MLOps tools such as MLflow, DVC, Kubeflow, Docker/Kubernetes, and GitOps practices Strong working knowledge of Azure and Databricks services Proficient with observability and monitoring tools (e.g. Prometheus, Grafana More ❯

analysis. Expertise in Python and the tools and libraries that make ML magic happen. Familiarity with ML experiment tracking and collaboration tools, such as Mlflow and Weights & Biases. A solid background in software engineering and DevOps practices, MLOps deployment, and infrastructure. A knack for generative AI frameworks and SDKs, like More ❯

NLP unstructured data. Implemented ML platform in enterprise client experience of ML use-cases AIML Platforms: DataRobot, Dataiku, Anaconda, Sagemaker, Vertex etc. AIML Frameworks: MLFlow, KubeFlow, BentoML, TensorFlow etc. AIML Development: PyTorch, Jupyter Notebooks, XGBoost, Tensorflow etc. AIML Models: Linear/Logistic Regression, KNN, Decision Trees, Anomaly Detection, LLMs, Generative More ❯

pressure Nice-to-Have: Experience with marketing data or customer-level models (e.g. uplift, attribution, causal inference, campaign optimization) Familiarity with MLOps tools (e.g. MLflow, FastAPI, Airflow) Exposure to A/B testing and experimentation frameworks WHY THIS ROLE IS DIFFERENT This isn’t a narrow data science role — you More ❯

audiences Nice-to-Have: Experience with marketing data, customer-level modelling, or decision science (e.g. uplift, attribution, causal AI, optimization) Familiarity with MLOps tooling (MLflow, FastAPI, Airflow, etc.) Experience designing and interpreting A/B tests or other experimental frameworks Background in consulting, agency, or fast-paced environments where autonomy More ❯

work reliably in the wild. You’ll: Build agentic LLM workflows that process and transform natural language input Set up pipelines (CI/CD, MLFlow, Azure) and versioning to keep models stable and up-to-date Implement monitoring, evaluation, and feedback loops that catch issues early Design AI tools that More ❯

PyQt): Develop or integrate user interfaces for internal tools or customer-facing applications. Model Monitoring & Experiment Tracking: Leverage tools like Weights & Biases (wandb) or MLflow to track experiments, monitor model performance, and ensure continuous improvement. Performance Optimization: Conduct performance tuning and hardware optimization (GPU/CPU) to achieve high throughput … with RESTful API design and implementation. Knowledge of PyQt (or similar frameworks) for desktop UI development. Familiarity with Model Monitoring & Experiment Tracking (Weights & Biases, MLflow, etc.). Strong background in linear algebra, calculus, and probability/statistics as they relate to ML. Excellent problem-solving and debugging skills. Bachelor’s … deployment and scaling. Understanding of Edge Computing and on-device model optimization (TensorRT, ONNX). Knowledge of NVIDIA CUDA for GPU acceleration. WANDB and MLflow for training monitoring. Contributions to open-source computer vision or deep learning projects. What We Offer Competitive Compensation Flexible Work Arrangements (Remote) and a positive More ❯

small project teams, and help recruit top talent as we grow. Technical Delivery: Provide hands-on support with Databricks notebooks, Delta Lake, Spark optimization, MLflow integration, and related areas when necessary. Business Development Support: Partner with sales and leadership teams to support presales activities, including client pitches, proposals, and solution More ❯

TGI, ensuring optimal performance and reliability. • Pipeline Engineering: Design and maintain automated pipelines for model finetuning, evaluation, versioning, and continuous delivery using tools like MLflow, SageMaker Pipelines, or Kubeflow. • Infrastructure Management: Architect and manage cloud-native, cost-effective infrastructure for machine learning workloads using AWS (SageMaker, EC2, EKS, Lambda) or … Strong programming proficiency in Python, with additional experience in C/C++ for performance-sensitive applications. • Tooling Knowledge: Proficiency in MLOps frameworks such as MLflow, Kubeflow, or SageMaker Pipelines; familiarity with Docker and Kubernetes. • Optimization Techniques: Hands-on experience with model performance optimization techniques and distributed training frameworks (e.g., DeepSpeed More ❯

???? Transform Healthcare with Cutting-Edge Tech! ???? Position: Data Engineer (Python/Databricks) Location: Remote Salary: Up to £80,000 + Benefits Are you driven by a passion for health tech and innovation? Do you dream of revolutionizing clinical research through More ❯

Machine Learning Engineer – Fintech - London Hybrid - City - 2 days We’re looking for an ML Engineer with MLOps and MLFlow experience to join an existing project with a leading Fintech. The role will be working on an existing AWS platform, looking to enhance real-time services focussed on low latency … for projects and will involve some stakeholder management. Key skills: Machine Learning experience Microservices architecture Realtime Services/API Python Docker Kubernetes Jenkins MLFlow Databricks Ideally, you’ll have experience within the Payments industry , but we’re looking for the skill set over the industry, so experience and understanding of More ❯