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Research Intern

Gensyn · Remote

Location
Remote
Workplace
Remote
Level
Internship
Posted
16 months ago

About this role

Machine intelligence will soon take over humanity’s role in knowledge-keeping and creation. What started in the mid-1990s as the gradual off-loading of knowledge and decision making to search engines will be rapidly replaced by vast neural networks - with all knowledge compressed into their artificial neurons. Unlike organic life, machine intelligence, built within silicon, needs protocols to coordinate and grow. And, like nature, these protocols should be open, permissionless, and neutral. Starting with compute hardware, the Gensyn protocol networks together the core resources required for machine intelligence to flourish alongside human intelligence.

The Role

  • Contribute to cutting-edge research in scalable, distributed machine learning systems alongside experienced researchers and engineers. Explore new ways of building and verifying neural networks that operate across huge, decentralised, topologies of heterogenous devices.

Responsibilities

  • Contribute to original research in deep learning with a focus on modular architectures, verifiability, continual learning, and scale
  • Design and prototype novel neural network architectures for decentralized compute environments
  • Contribute to joint publications and projects in collaboration with academic and industry researchers targeting top-tier AI venues such as NeurIPS, ICML, and ICLR

Competencies

Must Have

  • Currently enrolled in a PhD program (or, in exceptional cases, in a Master’s program) in Computer Science, Machine Learning, or a related field
  • Prior experience conducting original research, ideally with authorship or co-authorship on ML papers
  • Strong understanding of deep learning fundamentals and experience working with in at least one major framework, e.g. PyTorch, JAX, or TensorFlow
  • Self-directed, curious, and able to thrive in an environment with high autonomy
  • Excellent written and verbal communication skills

Preferred

  • Research experience in distributed systems, continual learning, or modular neural architectures
  • A desire to contribute to open research and collaborate with the broader ML research community

Nice to Have

  • Experience at the intersection of cryptography and machine learning

Please note: the benefits listed below apply to full-time employees only

Compensation / Benefits

  • Competitive salary + share of equity and token pool
  • Fully remote work - we currently hire between the West Coast (PT) and Central Europe (CET) time zones
  • Visa sponsorship - available for those who would like to relocate to the US after being hired
  • 3-4x all expenses paid company retreats around the world, per year
  • Whatever equipment you need
  • Paid sick leave and flexible vacation
  • Company-sponsored health, vision, and dental insurance - including spouse/dependents [🇺🇸 only]

Our Principles

Autonomy & Independence

  • Don’t ask for permission - we have a constraint culture, not a permission culture.
  • Claim ownership of any work stream and set its goals/deadlines, rather than waiting to be assigned work or relying on job specs.
  • Push & pull context on your work rather than waiting for information from others and assuming people know what you’re doing.
  • Communicate to be understood rather than pushing out information and expecting others to work to understand it.
  • Stay a small team - misalignment and politics scale super-linearly with team size. Small protocol teams rival much larger traditional teams.

Rejection of mediocrity & high performance

  • Give direct feedback to everyone immediately - rather than avoiding unpopularity, expecting things to improve naturally, or trading short-term pain for extreme long-term pain.
  • Embrace an extreme learning rate - rather than assuming limits to your ability / knowledge.
  • Don’t quit - push to the final outcome, despite any barriers.
  • Be anti-fragile - balance short-term risk for long-term outcomes.
  • Reject waste - guard the company’s time, rather than wasting it in meetings without clear purpose/focus, or bikeshedding.

As published by Gensyn. Applications are handled on their site.

Skills this posting mentions

Machine LearningTensorFlowDecision-Making

About Gensyn

The Gensyn network is the Machine Learning Compute Protocol that unites all of the world’s compute into a global machine learning supercluster, usable by anyone at any time.

All 3 openings at Gensyn

One click, then it is written

Apply to Gensyn with a resume written for this role.

Queue Research Intern and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Gensyn’s form for you.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

    Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.

  3. 03Each one is written up

    Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.

  • 25 sent a week, free
  • No card
  • Nothing sent until you say so

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Put this to work

Paste your career in once. Every application after that is written for you.

Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

    Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.

  3. 03Each one is written up

    Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.

  • New matches ranked and written before you are up.
  • Every bullet stays inside what your history supports. Nothing invented.
  • Queued, submitted, interviewing, offer: one screen, not a spreadsheet.

500 free credits on sign-up. No card. Nothing is sent until you say so.

Listed from the job board Gensyn publishes. Refolk is not the employer and does not handle their hiring. Applications go to Gensyn directly.