At a Glance
- Tasks: Architect AI systems and develop models for simulating atomic motion and liquid flow.
- Company: Orbital Industries, a leader in innovative AI solutions.
- Benefits: Competitive salary, flexible work options, and opportunities for research publications.
- Other info: Collaborative environment with a focus on impactful projects and career growth.
- Why this job: Join a cutting-edge team and push the boundaries of machine learning research.
- Qualifications: Experience in machine learning and a passion for innovative technology.
The predicted salary is between 72000 - 88000 £ per year.
Orbital Industries seeks a Machine Learning Research Engineer to architect cutting-edge AI systems for multi-scale design of physical technologies. You will develop foundation models to simulate atomic motion and macroscopic liquid flow, co-design across scales, and drive production-ready solutions with domain experts.
You will set high technical standards, deliver impactful AI projects across computational chemistry and agentic workflows, and push the frontier of ML research with publications.
Industrial AI ML Research Engineer — Scalable Systems employer: Orbital
At Orbital Industries, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. Our commitment to employee growth is evident through hands-on opportunities in cutting-edge AI technology and a supportive environment that encourages continuous learning. Located at the forefront of industrial AI, we offer unique advantages such as working with world-class teams and contributing to impactful projects that shape the future of manufacturing.
StudySmarter Expert Advice🤫
We think this is how you could land Industrial AI ML Research Engineer — Scalable Systems
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Orbital.
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We think you need these skills to ace Industrial AI ML Research Engineer — Scalable Systems
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Orbital, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Orbital. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Orbital
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Orbital!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
