ML Engineer

About Us

Materials contribute to 50% of global CO2 emissions, those critical to the net-zero transition such as magnets, semiconductors, hydrogen fuel, batteries are some of the biggest contributors. Yet, using conventional experimental techniques, we have only discovered a fraction of material possibilities.  We’re using AI to discover new and more sustainable materials.

We have raised over £3m to accelerate the change to net-zero materials through innovation and secured partnerships with international businesses.  Backed by top VC funds and leading institutions including Innovate UK, Google, Microsoft and AWS we are growing our team to transform the landscape of material development as we strive towards a more sustainable future. 

About the role

We are looking for a talented ML engineer to play a leading role in our ML sub-team, complimenting the current team’s expertise and expanding our platform’s capabilities in exciting new directions.

Responsibilities 

• Contribute to the design and implementation of general-purpose ML architecture and tools to be used by the ML team to build state-of-the-art ML models of materials.

• Apply data science and machine-learning to infer understanding from our datasets and predict novel materials. 

• Collaborate with our science team to identify goals for platform development, opening new avenues for scientific investigation. 

• Take on more responsibility and control as we grow as a company and scale up our technology. 

About you

We are looking for talented and, more importantly, passionate individuals who are motivated by the application of science and innovation to achieve net-zero materials. 

Essential - technical:

• Minimum 1st degree in Computer Science, Physical Science or a related field, or equivalent work experience.

• 2+ years experience building and deploying ML products in a team.

• Experience applying machine-learning and data science techniques to numerical problems (e.g., use of TensorFlow to train models of physical properties). 

• Experience using development collaboration tools for large multi-developer projects (e.g., git). 

·        Strong understanding of the mathematical foundations of machine-learning and data science. 

·        Understanding of scientific principles, their application in deep-tech and scale of impact in the world.

·        Appreciation of early-stage startups and the opportunities to expand your skillset.

Essential - personal:

• Comfortable quickly adapting to new situations, learning new skills, and working independently as a self-starter.

• Inquiring mind, aptitude for creative thinking and problem solving, and proactive, methodical, and organised approach.

• Excellent communicator, able to effectively convey information to technical and non-technical colleagues in both written and verbal formats.

• Proven track record of ability to work effectively in a team.

• Appreciation of the needs, priorities, and challenges faced by a start-up company.

• Right to live and work in the UK without sponsorship.

Desirable:

• Experience deploying models in a cloud environment. 

• Understanding of containerisation technology (e.g., Docker). 

• Understanding of issues in material sustainability and commitment to addressing them. 

• Advanced degree in a Physical Science, Computer Science, or a related field. 

• Peer-reviewed publications on relevant topics. 

• Ability in JavaScript, Fortran, or C++. 

Benefits of working with us:

📈 Stock Options: We value our employees and you to share in the success of the company. You will be a vested partner in our future achievements.

🌍 Shape the company's future: Joining us at this early-stage presents a unique opportunity to shape the direction of the company and have a meaningful impact as we continue to grow.

🏦 Future security: We are VC backed and have secured future funding. This stability provides you with confidence and assurance in your contribution to the business.

🌴 Flexible holidays: 33 days holiday/year which can be used on UK public holidays or one more convenient days for you.

🎂 Your birthday day off: Enjoy a well-deserved day off to celebrate and recharge.

💻 Flexible work arrangements: We operate on a hybrid model with an average of 3 days in office/week. Flexible working times can also be arranged.

📒 Continuous learning and growth: We’re pioneers in our field. You'll be encouraged to expand your knowledge and skills in new areas, keeping you at the forefront of industry advancements.

The recruitment process

Three stage interview process 

• Initial 45 min video call "get to know" and a live coding pop-quiz led by our CTO, Robert Forrest

• 1.5 hour in-person interview, at our London offices, to go into detail around tech & science and a chance to meet the broader team

• A final 30 minute culture interview led by our CCO, Nic Stirk

• Successful candidates will need to complete:

  • Belbin teams role profile (personality profile for which you’ll receive a full report) 

  • References from two separate employers 

  • DBS check 

Diversity statement:

Materials Nexus actively supports equality, diversity and inclusion and encourages applications from all sections of society.  Research suggests women only apply when they meet 100% of the criteria.  Our technical hiring data shows female applicants were 3 times more likely to proceed to first round interviews than male applicants.  We encourage you to apply even if you do not feel you are an exact fit to the spec as we are excited by diversity of experience and above all passion to make a difference.