Machine Learning Engineer
Machine Learning Engineer - AI for Advanced Materials - Oxford / Remote (UK)
(Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform)
Overview
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.
NC/LS/MLENG
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