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Machine Learning Engineer

Noir Consulting
Yarnton
3 weeks ago
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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)

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.

Our client is seeking Machine Learning Engineers with experience in some or all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies.

Join a team that’s fusing AI, science, and engineering to push the boundaries of what’s possible.


All Machine Learning Engineer positions come with the following 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

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