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Machine Learning Researcher

Company: Secondmind
Posted on: 25 January 2024
Location: Cambridge (Hybrid)
Salary: Competitive

Click here to apply

About Secondmind

Secondmind is the optimization engine for the software defined vehicle. From reducing design simulation time and calibration overhead, to continuously improving energy efficiency and performance throughout the vehicle lifecycle, Secondmind cloud-native advanced machine learning solutions help automotive engineers break through complexity barriers in vehicle design and development so they can design better cars faster and accelerate the transition to carbon-neutral mobility.

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 and engineers that explore innovative ideas that can improve the state of the art in Probabilistic modelling and Bayesian optimization.

We work in a highly collaborative research team, developing algorithms that are theoretically rigorous, yet scalable to domains of real-world complexity, with the aim of publishing papers at leading machine learning conferences. In the past four years our team has published over 75 papers and filed 10 patents (check our papers on our website). Labs missions also include contributing to internal product development and customer research projects, assisting in the application of cutting-edge machine learning research to real world problems.

What will you be responsible for?

You will be expected to develop your own research program, with a view to developing new tools and techniques for probabilistic models (e.g. Gaussian Processes, Bayesian Neural Networks, Neural Processes) and active learning (e.g. Bayesian Optimization, Multi-armed bandits, Reinforcement learning). You will actively engage in team collaborations to meet research goals and report your research findings both internally and externally.

You will also be expected to engage in cross-functional teams dedicated to product development and customer projects, leveraging your expertise to contribute to the application of active learning solutions to real world problems.

Finally, this position is also an 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?

We are open to applicants at all levels, from fresh PhD graduates to experienced team leads. 

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.

What we offer you

  • Competitive salary package commensurate with experience and achievements.
  • Opportunity to work in a growing, innovative company at the forefront of AI in automotive.
  • A collaborative, flexible and friendly work environment.
  • A platform for developing relationships with the industry’s key players and decision-makers.
  • Immersion in an inclusive, stimulating, and intellectually vibrant work environment.
  • Opportunities for personal and professional growth.
  • Contributory Salary Sacrifice Pension Scheme
  • 25 days annual leave, plus statutory bank holidays
  • Hybrid working approach within the UK
  • Stock Options scheme (where applicable)
  • Private Medical Insurance & Private Dental Cash Plan
  • Salary sacrifice electric bike-to-work scheme
  • Cambridge Botanic Garden membership
  • Shopping discount scheme
  • Social events, game nights and sports groups
  • On-site gym

We are an equal opportunities employer, and aim to ensure all candidates are treated equally and fairly through the application process and beyond. We actively encourage applicants from under-represented backgrounds, and encourage our people to bring their authentic, original, and best selves to work. If you require assistance or an accommodation through the interview process due to a disability, to apply for one of our roles, please contact our HR team at:

Job Location

The office is based in Central Cambridge, UK.

We offer a hybrid working environment, with a flexible work schedule to support a work life balance within the UK.

Click here to apply

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