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- Tasks: Design and deploy cutting-edge ML models that revolutionise advanced materials.
- Company: Join a fast-growing deep-tech company transforming manufacturing with AI.
- Benefits: Competitive salary, equity options, private healthcare, and generous training allowance.
- Why this job: Make a tangible impact on industries like aerospace and energy with your ML expertise.
- Qualifications: Experience in Python and ML frameworks; familiarity with cloud platforms and data visualisation.
- Other info: Flexible working, international collaboration, and a culture that values creativity and curiosity.
The predicted salary is between 36000 - 60000 £ per year.
We’re looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that’s reinventing how the world designs and makes advanced materials. By combining artificial intelligence, physics-based simulation, and cutting-edge 3D printing, our client is transforming the way metal components are conceived, tested, and produced — enabling breakthroughs in aerospace, energy, and beyond. This is a rare chance to apply your ML expertise to problems that have a tangible, physical impact — from inventing new alloys to optimising complex manufacturing processes. You’ll collaborate with leading data scientists, engineers, and materials researchers to build models that drive real-world innovation. Expect to design, validate, and deploy state-of-the-art ML pipelines that move seamlessly from concept to production. If you thrive in fast-paced, intellectually charged environments where every model could change an industry, you’ll fit right in.
Responsibilities
- Collaborate with data scientists, engineers, and materials researchers to design, validate, and deploy ML models and pipelines that move from concept to production.
- Develop and maintain scalable ML workflows using the specified tech stack (Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, CI/CD, MLOps).
- Apply Bayesian modelling and probabilistic programming techniques where appropriate to quantify uncertainty and improve decision making.
- Work with data visualization tools to communicate model results to technical and non-technical stakeholders.
- Contribute to the design of AI-enabled simulations and 3D printing workflows in collaboration with materials researchers.
- Participate in code reviews, testing, and deployment to ensure reliable production systems.
Qualifications
- Experience with Python and a strong background in ML frameworks (PyTorch, TensorFlow, Scikit-learn).
- Experience with ML tooling (MLflow, Airflow), containerization (Docker), and orchestration (Kubernetes).
- Proficiency with data libraries (Pandas, NumPy, SciPy) and data visualization.
- Experience with CI/CD, MLOps, and cloud platforms (Azure, AWS, GCP).
- Familiarity with Bayesian modelling and probabilistic programming.
- Version control (Git) and Agile methodologies.
Benefits
- Competitive salary with annual performance-based bonuses.
- Equity options — share in the company's long-term success.
- Private healthcare and comprehensive wellbeing package.
- Generous pension scheme (up to 8%).
- Dedicated R&D time to explore new technologies and research ideas.
- Annual training & conference allowance of £5,000 for personal development.
- Flexible and hybrid working — work where you’re most effective.
- Opportunities for international collaboration with teams in Europe, Asia, and the US.
- 25 days holiday plus your birthday off and extra days for long service.
- Regular team offsites, guest talks, and hack weeks to spark innovation.
- An open, supportive culture that values curiosity, creativity, and deep technical mastery.
Location and Salary
Location: Oxford, UK
Salary: £45,000-£80,000 (DOE) + Bonus + Equity + Pension + Benefits
Applicants must be based in the UK and have the right to work in the UK, even though remote working is available.
How to apply
To apply for this position please send your CV to Lina Savjani at Noir.
Machine Learning Engineer in Yarnton employer: Noir
Contact Detail:
Noir Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Yarnton
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even online forums related to machine learning. You never know who might have a lead on that perfect job or can give you insider tips.
✨Show Off Your Skills
Create a portfolio showcasing your projects and contributions. Whether it's GitHub repos or a personal website, let your work speak for itself. This is especially important in tech roles like Machine Learning Engineer where practical skills are key.
✨Ace the Interview
Prepare for technical interviews by practicing coding challenges and ML concepts. Brush up on your Python and frameworks like PyTorch and TensorFlow. We recommend mock interviews with friends or using platforms that offer practice sessions.
✨Apply Through Us!
Don’t forget to check out our website for the latest job openings. Applying directly through us not only gives you access to exclusive roles but also helps us match you with opportunities that fit your skills perfectly!
We think you need these skills to ace Machine Learning Engineer in Yarnton
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with the specific tech stack mentioned in the job description. We want to see how your skills in Python, PyTorch, and other tools can contribute to our mission.
Showcase Your Projects: Include any relevant projects or experiences that demonstrate your machine learning expertise. We love seeing real-world applications of your skills, especially if they relate to advanced materials or innovative manufacturing processes.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re excited about this role and how you can make an impact at StudySmarter. We appreciate enthusiasm and a clear connection to our goals.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at Noir
✨Know Your Tech Stack
Make sure you’re well-versed in the tech stack mentioned in the job description. Brush up on Python, PyTorch, TensorFlow, and other tools like Docker and Kubernetes. Being able to discuss your experience with these technologies confidently will show that you’re ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've applied machine learning to solve real-world problems. Think about how you’ve used Bayesian modelling or probabilistic programming in past projects. This will demonstrate your ability to tackle challenges similar to those faced by the company.
✨Communicate Clearly
Since you'll be working with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. Use data visualisation examples to illustrate your points. This will highlight your communication skills and your ability to bridge the gap between different teams.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's projects, culture, and future directions. Inquire about their approach to AI-enabled simulations or how they integrate feedback into their ML pipelines. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
