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🇬🇧 United Kingdom Corridor 🛡️ Verified Employer Direct Placement

Research Intern

🏢 InstaDeep 📍 London, England 💼 Company - Private
Currency:
£42,000 - £65,000
£3,500 - £5,417 / mo
Verified Corporate Employer (Authorized Corporate Employer)

This vacancy is published by an accredited employer with authorized corporate payroll and standard compliance adherence.

Transatlantic Cost of Living & Purchasing Power Benchmark

Verified Analytics
Location Base
London, England
Tier-1 UK Economic Zone
Est. Take-Home Pay
68% - 74% (After PAYE & NI)
Single tax filer baseline
Transatlantic Parity
1.0 GBP ≈ $1.28 USD Living Standard
Direct corporate benchmark

Position Overview & Specifications

Founded in 2014, InstaDeep is today an EMEA leader in decision-making AI products for the Enterprise, with headquarters in London, and offices in Paris, Berlin, Tunis, Lagos, Dubai, Cape Town and the USA. InstaDeep has been named among the Top 100 global AI startups for three consecutive years by CB Insights, as well as one of the 100 most promising B2B companies in Europe, by Sifted. We have created an environment that ensures a challenge by working closely with a broad spectrum of high-quality clients, pushing you to thrive in an environment that’s rarely tedious and always looking to push you to come up with outside-the-box solutions using cutting-edge technologies. In our mission to stay ahead of the curve, we are proud to partner with firms such as BioNTech SE, Google DeepMind, NVIDIA and Intel, and world-class universities such as MIT, Oxford, UCL, and Imperial College London. We are also an NVIDIA Elite Service Delivery Partner and Google Cloud Partner.


Are you looking for a research internship?


As anThe 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 excitingly alternative approach to solving the path-finding problem. Specifically, this is a combinatorial problem not too dissimilar to the travelling salesman problem, consisting of finding paths between different sets of nodes simultaneously, whilst meeting certain constraints, such as no overlapping of ways. 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, and 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


The research intern you must accomplish the following:

  • 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 the 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

Requirements:

  • 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 full-time employment in the UK

Our Diversity, Equity, and Inclusion commitments

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 by other than by joining our team?

At present we operate in a hybrid way allowing work from home or work from the office as per each individual’s preferences. We are continuing to review the situation with the well-being of InstaDeepers at the forefront of our minds.

Right to work: Please note you will require the legal right to work in the location you are applying for.

Any further questions please do not hesitate to contact us at: talent@instadeep.com

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Candidate Selection & Onboarding Process

1

Application & Resume Screening

Submit your tailored CV/Resume directly to the talent acquisition portal.

2

Technical & Competency Interviews

Virtual interviews with the hiring manager and multidisciplinary team.

3

Formal Offer & Benefits Negotiation

Written agreement outlining compensation, equity, retirement vesting, and relocation allowances.

4

Onboarding & Corporate Integration

Equipment provisioning, team orientation, and commencement of duties.

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Hiring Organization
InstaDeep

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Location: London, England
Eligibility: Verified Employer Direct Placement
Schedule: Company - Private
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