Machine Learning Researcher

We are managing this recruitment internally and respectfully request no agency inquiries.

Secondmind is an Equal Opportunity Employer committed to fair, equitable treatment throughout the recruitment process and beyond. We actively champion applications from all backgrounds because we believe the best work happens when people can bring their authentic, original, and best selves to the team. If you require accommodation or assistance throughout the interview process due to a disability, please contact [email protected] we are happy to help.

About Secondmind

Secondmind builds data-efficient engineering AI software that helps teams make better design and performance optimisation decisions faster. Our product reduces simulation and testing requirements without compromising quality, accelerating development and enabling more sustainable.

Our positive working culture is founded on a collaborative environment that encourages teamwork and innovation. We foster open communication and cross-functional collaboration, enabling diverse teams to work together to solve complex challenges. Our flexible workplace plan ensures a healthy work-life balance, accommodating various working styles and personal needs, whether through remote work options or adaptable schedules.

We also prioritize personal and professional growth by offering development opportunities, including training and mentorship. This nurturing environment empowers our employees to thrive, continuously learn, and contribute meaningfully to our mission of advancing system design and calibration with our data-efficient machine learning solutions.

Founded in 2016 and supported by investors such as Mazda Motor Corporation, Amadeus Capital, Atlantic Bridge and Cambridge Innovation Capital, Secondmind was recently recognized with the Automotive Testing Technology International 'Alternative Powertrain Test Innovation of the Year Award 2024'; selected for the Tech Nation Future Fifty scale-up program, and named by Bloomberg as one of the UK’s 25 Startups to Watch 2024.

About the role

This is an exciting opportunity to join a team at the forefront of artificial intelligence and machine learning. Secondmind Labs consists of researchers that explore innovative ideas that can improve the state of the art in Probabilistic modelling, active learning and related fields, and tackle real-world challenging problems.

We work in highly collaborative research teams, developing algorithms that are theoretically rigorous, yet scalable to domains of real-world complexity, with the aim of solving our customers’ challenges, as well as publishing papers at leading machine learning conferences. In the past four years our team has published over 80 papers and filed 10 patents (check our papers on our website).

Key responsibilities

• Develop your own research program, with a view to developing new tools and techniques for probabilistic models, Bayesian optimization and related fields.
• Engage in team collaborations to meet research goals and report your research findings both internally and externally.
• Contribute to internal product development and customer research projects, assisting in the application of cutting-edge machine learning research to real world problems.
• The opportunity to take an active role in the development of our open source libraries (for example, Trieste, GPflow and GPflux).
  

What skills, experience, and qualifications do you need to succeed in this role?

From fresh PhD graduates to experienced team leads, we are open to applicants at all levels.

What we primarily look for is a good fit with the team, a researcher that we can easily see collaborating with and that will enrich our collective knowledge.

Essential skills and experience:

• A PhD in a technical field or an equivalent level of experience, having published work in machine learning, statistics, or optimization conferences and/or journals.

In addition, the following would be an advantage:

• A background in decision making (Bayesian optimization, bandits, reinforcement learning, active learning) and / or probabilistic modelling and methods (Gaussian processes, Bayesian neural networks, Variational inference, etc).
• Experience in numerical programming (Python/NumPy/Tensorflow/PyTorch).
• Experience or interest in applying machine learning to solve real world problems in projects which could relate to Secondmind’s customers.
• Keen to work as part of a team, to review documents and code, and to provide constructive feedback.
• A passion to continuously develop your own machine learning and research skills, and to help others to improve theirs.

Please note that we are unable to offer visa sponsorship for this role, and candidates must have the full right to work in the UK without restriction.

Our culture - What we can offer you

We offer a working environment that is inclusive, stimulates innovation and continuous learning, and that thrives on growth and change.

Our culture is underpinned by our values; they are what we stand for, part of our DNA. They help us to attract and retain the right talent and customers, help us make the right decisions and clarify how we should all behave and treat one another, they are:

• Delight every customer (Customers)
• No bar too high (Excellence)
• Give more than take (Sustainability)
• Make the impossible, possible (Innovation)
• Celebrate differences, act as one (Inclusion)

We also offer a number of benefits including:

• Competitive salary - reviewed annually
• 25 days annual leave, plus statutory bank holidays
• TGIF: Last friday of every month is a half day
• Enhanced family leave policies
• Salary Sacrifice Pension Scheme
• Life Assurance of 4x salary
• Private Medical Insurance
• Eyecare Policy
• Dental Cash Plan
• Stock Options (where applicable)
• Free 24 hour access on-site gym
• Discount Shopping & Wellbeing Platform
• Employee Assistance Programme
• Values Award Scheme
• Cambridge Botanic Garden membership
• Social events, game nights and sports groups

Contact

If you have any questions on the specifics of this role, please contact [email protected]