Research Intern

Gensyn

Completely RemoteInternshipInformation Technology
Posted Today

Job description

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 targeting top-tier AI venues such as NeurIPS, ICML, and ICLR

Requirements

  • Currently enrolled in a PhD program (or exceptional Master’s) in Computer Science, Machine Learning, or related field
  • Prior experience conducting original research with authorship on ML papers
  • Strong understanding of deep learning fundamentals
  • Experience with at least one major framework such as PyTorch, JAX, or TensorFlow
  • Self-directed with ability to thrive in high-autonomy environments
  • Excellent written and verbal communication skills

Preferred Qualifications

  • Research experience in distributed systems, continual learning, or modular neural architectures
  • Desire to contribute to open research and collaborate with the broader ML community
  • Experience at the intersection of cryptography and machine learning

Benefits

  • Competitive salary plus equity and token pool
  • Fully remote work across PT to CET time zones
  • Visa sponsorship available for US relocation
  • 3–4 all-expenses-paid company retreats per year
  • Equipment stipend
  • Paid sick leave and flexible vacation
  • Health, vision, and dental insurance for US employees and dependents

About the Company

Gensyn is building a decentralized protocol that networks compute hardware to provide the core resources required for machine intelligence to flourish alongside human intelligence.

Skills & tools

PyTorchJAXTensorFlowDeep LearningDistributed SystemsMachine Learning

What the team is looking for

Use this list as a quick fit check before you apply.

  1. 01Currently enrolled in a PhD in Computer Science, Machine Learning, or related field
  2. 02Original ML research experience with publications
  3. 03Strong understanding of deep learning fundamentals
  4. 04Experience with PyTorch, JAX, or TensorFlow
  5. 05Self-directed with high autonomy
  6. 06Excellent written and verbal communication skills
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