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For Companies At a Glance
- Tasks: Design and develop innovative ML models to optimise manufacturing processes.
- Company: Fast-growing tech company revolutionising advanced metal components.
- Benefits: Competitive salary, excellent benefits, and flexible hybrid working options.
- Why this job: Join a multidisciplinary team and make a real impact in materials innovation.
- Qualifications: Bachelor's in STEM, strong Python skills, and ML model experience required.
- Other info: Dynamic, agile environment with opportunities for career growth.
The predicted salary is between 36000 - 60000 £ per year.
Oxford - Some flexibility on the working times and potential for some hybrid working for the right candidate. Competitive salary and excellent benefits.
Join a fast-growing, venture-funded technology company developing the next generation of advanced metal components. Our multidisciplinary team of metallurgists, engineers, and software developers works across the UK, Japan, and the US, using cutting-edge machine learning and physical modelling to accelerate materials innovation and transform manufacturing.
Role Overview
We are seeking a Machine Learning Engineer to design, develop, and validate novel ML models that optimise manufacturing processes and material composition. You will collaborate closely with process engineers and materials scientists, identifying meaningful features and translating complex datasets into impactful insights. You will also help advance our internal ML platforms to support model adoption and scale.
In This Role, You Will:
- Build robust ML and MLOps pipelines for scalable, reproducible model development, deployment, and monitoring.
- Use tools such as Airflow for workflow orchestration and MLflow for experiment tracking, model registry, and lifecycle management.
- Work within an agile development environment and help prioritise high-value opportunities for rapid delivery.
Essential Skills:
- Bachelor's degree (2:1 or above) in a STEM field.
- Strong Python development skills.
- Hands-on experience developing ML and/or deep learning models for scientific or engineering problems.
- Experience with MLOps tools such as Airflow, MLflow, and containerisation (e.g., Docker).
- Strong data-visualisation and storytelling skills.
- Interest in materials discovery, computer vision, big data, or optimisation.
- Collaborative communicator, organised, proactive, and curious.
Desired Skills:
- Master's degree in ML, mathematics, or statistics.
- Knowledge of probabilistic and Bayesian modelling.
- Solid software-engineering principles and experience with an OO language.
- Familiarity with cloud platforms (Azure, AWS, or GCP) and IaC tools such as Terraform.
Machine Learning Engineer in Oxford employer: Perfect Storm Software, LLC
Contact Detail:
Perfect Storm Software, LLC Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Oxford
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those that relate to manufacturing or materials science. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in machine learning. Be ready to discuss your experience with tools like Airflow and MLflow, as well as how you've tackled real-world problems.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Machine Learning Engineer in Oxford
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your Python skills, MLOps experience, and any relevant projects you've worked on. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about machine learning and how you can contribute to our team. Be sure to mention any specific experiences that relate to materials innovation or manufacturing.
Showcase Your Projects: If you've worked on any ML projects, make sure to include them in your application. Whether it's a personal project or something from your studies, we love seeing practical examples of your skills in action!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the latest updates about your application status. Plus, it’s super easy!
How to prepare for a job interview at Perfect Storm Software, LLC
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts and tools. Be ready to discuss your experience with Python, MLOps tools like Airflow and MLflow, and any projects where you've developed ML models. This is your chance to show off your technical skills!
✨Show Your Collaborative Side
Since the role involves working closely with process engineers and materials scientists, be prepared to talk about your teamwork experiences. Share examples of how you've effectively communicated complex ideas and collaborated on projects. This will highlight your ability to fit into their multidisciplinary team.
✨Prepare for Problem-Solving Questions
Expect to face some technical challenges during the interview. Think through potential scenarios where you might need to optimise manufacturing processes or analyse complex datasets. Practising these problem-solving questions can help you articulate your thought process clearly.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about their current ML projects, the tools they use, or how they envision the future of materials innovation. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
