Senior Machine Learning Ops Engineer

Fully remote – Up to £120,000+ depending on experience

This organisation uses a combination of AI, edge computing, and scalable sensor fusion technology to create automated systems.

If you love to:

• Build and integrate end to end lifecycles of large-scale, distributed machine learning systems using the latest open-source technologies.
• Develop and deploy scalable tools and services to handle ML model training, containerization, deployment, and monitoring.
• Identify and evaluate new patterns and technologies to improve performance, maintainability, and elegance of our machine learning systems.
• Build software that improves the rate of experimentation, with emphasis on reproducibility and auditability, and supports decision making regarding the overall ML system design.
• Apply software engineering best practices to machine learning, including documentation, CI/CD, unit testing etc.
• Collaborate with engineers across functions to solve complex data problems at scale.
• Lead technical projects to completion. Communicate with peers to build requirements and track progress.

We are seeking a Senior with:

• Significant full-time experience building end to end ML systems as an ML engineer, Platform engineer or equivalent.
• Proficiency in developing and deploying with containers and container-orchestration tools (Kubernetes, Docker etc.)
• Experience with monitoring and analytics tools for infrastructure and cloud services (Datadog, Prometheus, Grafana etc.)
• Experience with ML task orchestration tools (Kubeflow, Airflow, Argo etc.)
• Solid software engineering skills in complex, multi-language systems. Fluency in Python and bash scripting

• Strong understanding of ML algorithms and deep learning basic concepts and principles
• Experience with ML modelling frameworks (PyTorch, scikit-learn etc.), and inference-optimised

ML runtimes (TensorRT, ONNX, OpenVINO etc.)

• Experience with cloud service providers (Azure, AWS etc) and Azure Databricks

If you have one of these experiences, it is even better:

• Experience working with cloud data processing technologies (Spark, SQL, etc.)
• Knowledge of Go, C++ or CUDA
• Experience in optimizing GPU utilization (Nvidia MPS, MIG, time-slicing etc.)

If you’re looking for a new, exciting challenge and are interested in using your knowledge and creativity to make a meaningful impact, reach out to me at [email protected].