Senior Machine Learning Engineer
- Design and implement production-ready ML systems for time-series data and object detection, working closely with cross-functional teams of data scientists and engineers
- Architect and build ML pipelines and infrastructure for an automated Solution Engine, including live, batch and synthetic data
- Design and implement scalable infrastructure for LLM deployments, including capacity planning, error handling, and performance optimi s ation
- Create reusable tools and frameworks to streamline ML deployment processes across diverse use cases including signal processing, object detection, RAG systems, and reinforcement learning
- Mentor and manage junior team members in ML engineering best practices and foster a collaborative, innovative environment
- Pursue continuous learning and stay abreast of emerging trends in MLOps, cloud architecture, and deployment strategies across Defence applications
- Strong software engineering background with extensive experience in implementing production ML systems
- Strong understanding of MLOps practices and the full machine learning lifecycle
- Experience building ML pipelines and infrastructure from the ground up, including recent developments, e.g. MCP.
- Experience with containerization (Docker) and orchestration (Kubernetes)
- Proficiency with cloud platforms and MLOps tools; Azure preferred
- Experience with computational resource planning and troubleshooting for high-demand local ML model serving (including handling rate limiting challenges)
- Excellent communication skills, able to bridge technical gaps between data scientists, engineers and deployed operators
- Collaborative mindset and ability to work effectively in a fast-paced, innovative environment
- Prior Defence or Aerospace experience preferred but not essential
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