Staff Machine Learning Engineer
Orbital
full-time
Posted on:
Location Type: Hybrid
Location: London • United Kingdom
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Job Level
About the role
- Set the technical bar and ensure engineering excellence
- Establish and maintain exceptionally high standards for code quality, system architecture and ML research and engineering practices through hands-on coding and technical review
- Design robust, well-engineered systems that others can build upon, balancing research velocity with production requirements
- Drive technical decisions on model selection, training approaches and deployment strategies
- Deliver high-impact AI projects across diverse domains
- Develop and deploy AI solutions across the entire technology development pipeline- computational chemistry simulations, agentic workflows and beyond
- Rapidly upskill in new technical areas through close collaboration with domain experts (no prior chemistry or materials experience required)
- Demonstrate strong implementation skills through hands-on development, contributing significantly to the codebase
- Balance research rigour with pragmatic engineering to deliver production-ready systems at scale
- Push the frontier of ML research
- Design and implement novel ML architectures for complex scientific domains, with work that meets publication standards at top-tier conferences
- Drive research projects from conception through to deployment, showing initiative and technical depth
- Engage continuously with the latest ML literature, staying current with developments in foundation models, generative AI and scientific machine learning
Requirements
- ONE of:
- 5+ years of professional experience in ML/AI research or engineering.
- A relevant PhD + 2 years of professional experience in ML/AI research or engineering.
- Proven experience training, evaluating and productionising AI models at scale, with deep understanding of the full ML lifecycle from research to deployment
- Strong engineering fundamentals with the ability to write high-quality, maintainable code and architect robust systems
- A strong ability to reason about algorithms, system design, linear algebra, probabilistic concepts and ML engineering trade-offs
- An ability to debug complex machine learning systems through meticulous attention to detail, testing of edge cases and carefully selected ablations
- A genuine interest in building AI systems that enable breakthrough scientific and industrial applications
- Upon reading Hamming's You and Your Research, you resonate with quotes such as:
- "Yes, I would like to do first-class work"
- "You should do your job in such a fashion that others can build on top of it, so they will indeed say, 'Yes, I've stood on so and so's shoulders and I saw further.'"
- "Instead of attacking isolated problems, I made the resolution that I would never again solve an isolated problem except as characteristic of a class
- **Bonus:** Experience with physics-informed or chemistry-focused AI applications. Experience building or fine-tuning large language models. Experience with agent-based systems, tool use or agentic workflows. Contributions to open-source ML projects or published research.
Benefits
- Orbital is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningartificial intelligencemodel selectiontraining approachesdeployment strategiessystem architecturecode qualityalgorithm reasoninglinear algebraprobabilistic concepts
Soft Skills
attention to detailinitiativecollaborationstrong implementation skillsability to reasonproblem-solvingcommunicationresearch rigoradaptabilitycritical thinking