At a Glance
- Tasks: Join a multidisciplinary team to develop and implement machine learning solutions for real-world challenges.
- Company: Mind Foundry, a leader in AI and ML for Defence and National Security.
- Benefits: Flexible hybrid working, competitive salary, private healthcare, and generous leave.
- Why this job: Make a real impact on safety and resilience while developing your technical skills.
- Qualifications: Degree in STEM, familiarity with ML libraries, and programming experience in Python.
- Other info: Supportive environment with opportunities for professional growth and client engagement.
The predicted salary is between 28800 - 48000 Β£ per year.
We are looking for a Graduate Machine Learning Engineer to join our supportive, multidisciplinary team and contribute to the development and application of machine learning solutions for our clients and products. You will help explore, prototype, and implement AI/ML approaches to problems both within and outside our core product offering. Working at the forefront of AI and ML alongside experts in a range of disciplines, you will help users defend against Defence & National Security threats and directly contribute to safer, more resilient systems in the real world.
Mind Foundry works on some of the most complex and urgent challenges in Defence and National Security. We specialise in supporting customers across the community to make sense at the speed of relevance from the ever-increasing volumes of data collected by sensors and systems. Work is challenging, customers need products and applications they can trust, and the sense of achievement is substantial. This role provides an excellent opportunity to develop your technical skills, apply academic knowledge in a real-world commercial environment and gain exposure to client-facing work. The role can be office-based or hybrid; you are expected to work from our Summertown, Oxford office at least one day per week and travel to client sites and partner locations as needed.
Areas of Impact
- Work closely with colleagues across Science and Engineering, and Product teams to develop, test and implement ML algorithms that solve complex, real-world problems efficiently and at scale.
- Apply established machine learning techniques and libraries to real-world datasets, with support and mentorship from senior team members.
- Follow best practices in scientific experimentation, validation, and documentation.
- Contribute to technical documentation, internal notes, and project reports.
- Attend client meetings to understand customer needs and how solutions are delivered.
- Take part in knowledge sharing, training, and professional development activities, including attending relevant events or conferences to stay current with emerging ML technologies and techniques and support innovation within the team.
Core Skills & Experience
- A degree (or expected degree) in Computer Science, Applied Mathematics, Statistics, Physics, or a related STEM field.
- Familiarity with modern machine learning libraries (e.g. PyTorch or TensorFlow) through coursework, projects, internships or extra-curricular activity.
- Experience programming in Python in an academic or project-based context.
- An interest in building practical systems that help users understand and benefit from machine learning models.
- A strong foundation in scientific thinking, with an appreciation for experimental rigor and validation.
- A willingness to learn, ask questions, and work collaboratively as part of a team.
- An interest in working alongside our clients to understand and solve their complex problems.
Desirable
- Exposure to working with larger datasets and basic data engineering concepts.
- Awareness of Agile or iterative development approaches.
- Experience with additional programming languages (e.g. Java, JavaScript/TypeScript).
- The ability to explain technical ideas clearly, with guidance, to both technical and non-technical audiences.
What We Offer
We believe in investing in our people by encouraging career and personal development that aligns with your goals and ambitions. We make sure all staff have the tools, time and support they need to shape their own professional development. We want to help you excel at what you do and support your growth within the company. Competitive compensation package and benefits include:
- Hybrid working (some roles may require full-time onsite attendance).
- Flexible hours.
- Professional and personal development.
- 25 days of annual leave (plus Bank Holidays and a company-wide break over Christmas).
- Salary Sacrifice Pension scheme with a 5% employer contribution (minimum 5% employee contribution).
- Private Healthcare (including dental and optical cover).
- Group Life Cover at three times your annual salary once you pass your probation period.
- Enhanced Parental and Sickness Leave.
- Home Office Setup Allowance.
- Workplace Nursery Scheme.
- Pet-friendly office.
For more information, please visit our website www.mindfoundry.ai or email recruitment@mindfoundry.ai. While we think the above experience is important, weβre keen to hear from people that believe they have valuable skills, ideas, or perspectives that will make an impact in this role. If our team and mission resonate with you, but you do not necessarily meet all of our requirements, we still encourage you to apply.
Graduate Machine Learning Engineer in Oxford employer: Mind Foundry Ltd
Contact Detail:
Mind Foundry Ltd Recruiting Team
StudySmarter Expert Advice π€«
We think this is how you could land Graduate Machine Learning Engineer in Oxford
β¨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with alumni from your university. You never know who might have a lead on a job or can give you insider info about the company.
β¨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning. Share it on platforms like GitHub and make sure it's easy for potential employers to see what you can do.
β¨Tip Number 3
Prepare for interviews by practising common technical questions and coding challenges. Use resources like LeetCode or HackerRank to sharpen your skills. Remember, confidence is key, so practice makes perfect!
β¨Tip Number 4
Apply through our website! Itβs the best way to ensure your application gets seen. Plus, we love hearing from candidates who are genuinely interested in joining our team and contributing to exciting projects.
We think you need these skills to ace Graduate Machine Learning Engineer in Oxford
Some tips for your application π«‘
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Graduate Machine Learning Engineer role. Highlight any relevant projects or coursework that showcase your familiarity with machine learning libraries like PyTorch or TensorFlow.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about machine learning and how your background makes you a great fit for our team. Donβt forget to mention any client-facing experiences or teamwork that demonstrate your collaborative spirit!
Showcase Your Projects: If you've worked on any machine learning projects, whether in academia or as personal endeavours, make sure to include them. We love seeing practical applications of your skills, so share what youβve built and the impact it had!
Apply Through Our Website: We encourage you to apply directly through our website. Itβs the best way for us to receive your application and ensures youβre considered for the role. Plus, it shows us youβre keen to join our team!
How to prepare for a job interview at Mind Foundry Ltd
β¨Know Your ML Basics
Brush up on your machine learning fundamentals before the interview. Be ready to discuss key concepts, algorithms, and libraries like PyTorch or TensorFlow. This will show that you have a solid foundation and are eager to apply your knowledge in real-world scenarios.
β¨Showcase Your Projects
Prepare to talk about any relevant projects or coursework where you've applied machine learning techniques. Highlight your role, the challenges you faced, and how you overcame them. This demonstrates your practical experience and problem-solving skills.
β¨Ask Insightful Questions
During the interview, donβt hesitate to ask questions about the teamβs current projects or the technologies they use. This shows your genuine interest in the role and helps you understand how you can contribute effectively.
β¨Emphasise Collaboration
Since the role involves working closely with various teams, be prepared to discuss your teamwork experiences. Share examples of how you've collaborated with others to achieve a common goal, as this will highlight your ability to work in a multidisciplinary environment.