Orbital Industries
Machine Learning Engineer
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Machine Learning Engineer
Machine Learning Engineer – Orbital
Orbital is an AI-first industrial company building hardware from the atoms up. Our goal is to lead an industrial renaissance to advance critical technologies and secure our planet for generations to come.
We’re starting with critical hardware for AI data centers to make them more performant and sustainable. Every Orbital product is invented with our AI platform — uniting AI-automated hardware engineering with AI-designed material science to achieve breakthrough real-world performance.
We have an ambitious mission and need excellent people in all our teams - AI research, operations, advanced materials, mechanical engineering, chemical engineering and manufacturing.
Working at Orbital means working in tightly integrated, vertically integrated teams. We’re looking for people who have a love of physical technology, curiosity in AI and a desire to learn.
About the Role
As a Machine Learning Engineer at Orbital, you will architect cutting-edge AI systems for the multi-scale design of physical technologies. When we say multi-scale, we mean it: we build world-class foundation models for simulating both:
- The microscopic motion of atoms
- The macroscopic flow of liquids in 1GW data centers
We then co-design across these different scales using the ingenuity of our scientists and engineers, augmented with best-in-class domain agents.
In this role, you will:
- Set exceptionally high technical standards
- Drive projects from prototype through to production deployment
- Work with someone who has a love of craftsmanship, continual learning, and building systems that scale
- Value low ego, and a genuine passion for using AI to solve major global industrial technology challenges
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Key Responsibilities
1. 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 reviews
- Design robust, well-engineered systems that others can build upon, balancing research velocity with production requirements
- Drive technical decisions on:
- Model selection
- Training approaches
- Deployment strategies
2. Deliver high-impact AI projects across diverse domains
- Develop and deploy AI solutions across the entire technology development pipeline, including:
- Computational chemistry simulations
- Agentic workflows
- 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 and significant contributions to the codebase
- Balance research rigour with pragmatic engineering to deliver production-ready systems at scale
3. Push the frontier of ML research
- Design and implement novel ML architectures for complex scientific domains, with output meeting publication standards at top-tier conferences
- Drive research projects from conception through to deployment, showing initiative and technical depth
- Continuously engage with latest ML literature, staying current with developments in:
- Foundation models
- Generative AI
- Scientific machine learning
Requirements
We’re looking for someone who:
- Has significant software engineering and ML experience, with depth in training, evaluating, and deploying AI models — demonstrated through industry work
- Proven experience in:
- Training, evaluating, and productionising AI models at scale
- Deep understanding of the full ML lifecycle, from research to deployment
- Strong engineering fundamentals, including:
- Ability to write high-quality, maintainable code
- Skills to architect robust systems
- Strong technical reasoning about:
- Algorithms
- System design
- Linear algebra
- Probabilistic concepts
- ML engineering trade-offs
- Ability to debug complex ML systems with:
- Meticulous attention to detail
- Testing of edge cases
- Carefully selected ablations
- A genuine interest in building AI systems that enable breakthrough scientific and industrial applications
- Resonates with Hamming’s You and Your Research 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, make the resolution that you would never again solve one except as characteristic of a class."
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Bonus experience: Any of the following is advantageous but not required:
- Physics-informed or chemistry-focused AI applications
- 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
Orbital is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
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