Research Intern
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San Francisco, CA
🧪
Internship
InstaDeep, founded in 2014, is a pioneering AI company at the forefront of innovation. With strategic offices in major cities worldwide, including London, Paris, Berlin, Tunis, Lagos, Cape Town, Boston, and San Francisco, InstaDeep collaborates with giants like Google DeepMind and prestigious educational institutions like MIT, Stanford, Oxford, UCL, and Imperial College London. We are a Google Cloud Partner and a select NVIDIA Elite Service Delivery Partner. We have been listed among notable players in AI, fast-growing companies, and Europe's 1000 fastest-growing companies in 2022 by Statista and the Financial Times. Our recent acquisition by BioNTech has further solidified our commitment to leading the industry.
Join us to be a part of the AI revolution!
The internship will take the form of a novel research project with InstaDeep’s engineering team (applied research). In collaboration with, and guided by, other research engineers you will develop a new and interesting alternative approach to solving the path-finding problem. Specifically, this is a combinatorial problem not too dissimilar to the traveling salesman problem, consisting of finding paths between different sets of nodes simultaneously, whilst meeting certain constraints, such as no overlapping of paths.
The internship’s duration is usually at least 6 months.
In the first phase you will implement a new simple simulation environment to support the solution framing. From here you will develop optimisation-based solutions to understand the problem better and obtain a baseline. Following on, you will investigate incorporating cutting edge deep learning and reinforcement learning techniques (and combinations thereof) in innovative ways to improve performance.
You will be responsible for writing high-quality code, running well thought-out experiments, as well as documenting and communicating your findings to the wider team. Depending on project outcomes and wider team developments, you may be required to investigate different research avenues or contribute to work on any of the engineering team’s products in development.
Keywords: Machine Learning, Reinforcement Learning, Deep Learning, Path-finding, Research
Internship Responsabilities
We empower individuals to celebrate their uniqueness here at InstaDeep. Our team comes from all walks of life, and we’re proud to continue encouraging and supporting applicants from underrepresented groups across the globe. Our commitment to creating an authentic environment comes from our ability to learn and grow from our diversity, and how better to experience this than by joining our team? We operate on a hybrid work model with guidance to work at the office at least 2 to 3 days per week to encourage close collaboration and innovation. We are continuing to review the situation with the well-being of InstaDeepers at the forefront of our minds.
Right to work: Please note that you will require the legal right to work in the location you are applying for.
Join us to be a part of the AI revolution!
The internship will take the form of a novel research project with InstaDeep’s engineering team (applied research). In collaboration with, and guided by, other research engineers you will develop a new and interesting alternative approach to solving the path-finding problem. Specifically, this is a combinatorial problem not too dissimilar to the traveling salesman problem, consisting of finding paths between different sets of nodes simultaneously, whilst meeting certain constraints, such as no overlapping of paths.
The internship’s duration is usually at least 6 months.
In the first phase you will implement a new simple simulation environment to support the solution framing. From here you will develop optimisation-based solutions to understand the problem better and obtain a baseline. Following on, you will investigate incorporating cutting edge deep learning and reinforcement learning techniques (and combinations thereof) in innovative ways to improve performance.
You will be responsible for writing high-quality code, running well thought-out experiments, as well as documenting and communicating your findings to the wider team. Depending on project outcomes and wider team developments, you may be required to investigate different research avenues or contribute to work on any of the engineering team’s products in development.
Keywords: Machine Learning, Reinforcement Learning, Deep Learning, Path-finding, Research
Internship Responsabilities
- Work alongside research engineers in the engineering team, investigating approaches to solving the path-finding problem
- Implement a new simple environment to support the solution framing
- Investigate purely optimisation-based techniques and establish baseline performance
- Extend the investigation to use deep-RL or other cutting-edge machine learning techniques
- Research and keep on-top of latest developments in the area that might be relevant
- Be methodical and thorough about running and documenting experiments
- Produce good quality code, using software engineering best practices
- Report on, and present progress and findings, clearly and effectively
- Undergraduate or graduate degree in Computer Science, Mathematics or a related scientific field
- Highly motivated and willing to tackle new unexplored challenges with limited supervision
- Knowledge in, and ideally experience with, deep learning and reinforcement learning
- Experience developing and debugging in Python (familiarity with OOP a plus)
- Experience using deep learning frameworks such as PyTorch, Tensorflow and/or Jax.
- Research and software engineering experience demonstrated via previous work experience, internships, contributions to open source projects, or coding competitions.
- Excellent communication skills in English
- Work permit for internship time employment in the US
We empower individuals to celebrate their uniqueness here at InstaDeep. Our team comes from all walks of life, and we’re proud to continue encouraging and supporting applicants from underrepresented groups across the globe. Our commitment to creating an authentic environment comes from our ability to learn and grow from our diversity, and how better to experience this than by joining our team? We operate on a hybrid work model with guidance to work at the office at least 2 to 3 days per week to encourage close collaboration and innovation. We are continuing to review the situation with the well-being of InstaDeepers at the forefront of our minds.
Right to work: Please note that you will require the legal right to work in the location you are applying for.