Hybrid Senior Machine Learning Engineer

at Orbital

• Job title: Senior Machine Learning Engineer
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Location requirements: Hybrid, London, United Kingdom

About the role

• Senior Machine Learning Engineer designing AI systems for multi-scale physical technologies at Orbital. Leading high-risk projects with a focus on AI research and engineering excellence.

Responsibilities

• Define the technical direction for AI systems powering the multi-scale design of physical technologies
• Establish and maintain exceptionally high standards for code quality, system architecture and ML research and engineering practices across multiple teams, through hands-on coding, technical review and architectural leadership
• Design robust, well-engineered systems that set the standard for the organisation, balancing research velocity with production requirements
• Drive and influence technical decisions on model selection, training approaches and deployment strategies across the company’s ML efforts, articulating trade-offs to both technical and non-technical stakeholders
• Take ownership of ambiguous, high-risk, cross-functional projects, driving them from inception to completion and coordinating across multiple teams and domains
• Develop and deploy AI solutions across the entire technology development pipeline- computational chemistry simulations, agentic workflows and beyond with responsibility for end-to-end project outcomes
• Rapidly upskill in new technical areas through close collaboration with domain experts, and enable others to do the same (no prior chemistry or materials experience required)
• Perform sophisticated analysis and interpretation of complex datasets, communicating insights and their implications to influence organisational direction
• Design and implement novel ML architectures for complex scientific domains, with work that meets publication standards at top-tier conferences and defines new research directions for the team
• Stay current with state-of-the-art research and contribute to research discussions, providing insights on new developments that influence the team’s research agenda
• Drive research projects from conception through to deployment, showing initiative, technical depth and the ability to make judgment calls on high-uncertainty problems

Requirements

• Extensive AI/ML research and software engineering experience, with a track record of leading complex projects and influencing technical direction — demonstrated through sustained research contributions, senior industry roles, or a combination of both
• Proven track record of leading and delivering high-impact, ambiguous ML/AI projects 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 that set organisational standards
• A strong ability to reason about algorithms, system design, linear algebra, probabilistic concepts and ML engineering trade-offs — and to communicate these effectively to influence technical direction
• An ability to debug complex machine learning systems through meticulous attention to detail, testing of edge cases and carefully selected ablations
• Demonstrated ability to mentor and develop engineers, with evidence of shaping others’ technical growth and career trajectories
• A genuine interest in building AI systems that enable breakthrough scientific and industrial applications
• 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. Experience influencing technical strategy at an organisational level.

Benefits

• Orbital is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.