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Senior Machine Learning Ops Engineer

Up to £120,000+ DOE

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].

Becky Gorringe

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