Machine Learning Engineer - Intern

Posted 17 Days Ago
Be an Early Applicant
2 Locations
In-Office or Remote
Internship
Artificial Intelligence • Information Technology • Software
The Role
Work on Agora, a production decentralized training system: design and ship a scoped project, improve concurrent/parallel components, run multi-node training on cloud (AWS/GCP), contribute to production codebase, and present results to engineering and research teams during a 3-month internship.
Summary Generated by Built In

Pluralis Research is pioneering Protocol Learning - a fully decentralised way to train and deploy AI models that opens this layer to individuals rather than well resourced corporates. By pooling compute from many participants, incentivising their efforts, and preventing any single party from controlling a model's full weights, we're creating a genuinely open, collaborative path to frontier-scale AI.

As a Machine Learning Engineer Intern, you'll work on Agora - our production decentralised training system - alongside the engineers running real multi-node training at scale. This is a fixed-term internship (3 months, with option to extend). Intern projects are well-scoped pieces of our live roadmap, not side experiments: you'll ship real work in week one and own a genuine open problem by the end of your internship.

Key Responsibilities
  • Design, build and ship a well-scoped project on the Agora roadmap, with a final presentation to both the engineering and research teams.

  • Build and improve concurrent and parallel systems components (multiprocessing, async I/O and threading) within a production distributed training stack.

  • Work hands-on with large-scale training infrastructure across cloud providers (AWS/GCP).

  • Contribute to the production codebase daily: code review and mentorship from a buddy on the Agora team

What We're Looking For
  • Current enrolment in (or recent completion of) a Masters or PhD in machine learning, computer science or a related field. Engineering-inclined candidates from either level are welcome.

  • A genuine ML background. You can keep pace with a research-driven team, not just a strong generalist engineering profile.

  • Strong Python and PyTorch.

  • Experience building concurrent or parallel systems (multiprocessing, async I/O, threading).

  • Hands-on exposure to distributed machine learning, via internship, coursework or serious projects.

  • Experience working with AWS, GCP or other hyperscalers.

  • Australia-based.

Nice to Have
  • Top-tier ML publications (welcome, but not required for systems-focussed candidates).

  • Open-source contributions to ML frameworks, distributed systems or networking libraries.

FYI's
  • This internship is for Australia-based candidates only.

  • Applicants must have professional-level English proficiency (written and spoken).

  • Pluralis is a remote team across Australia and the US. You'll need to be comfortable working across timezones and collaborating with a diverse, distributed group.

  • Recruiters: we aren't looking for agency support at this time. We'll reach out if we need help.

Backed by Union Square Ventures and other tier-1 investors, we're a world-class, deeply technical team of ML researchers. Pluralis is unapologetically ideological. We view the world as a better place if we are able to implement what we are attempting, and Protocol Learning as the only plausible approach to preventing a handful of massive corporations monopolising model development, access and release, and achieving massive economic capture. If this resonates, please apply.

Skills Required

  • Current enrolment in or recent completion of a Masters or PhD in machine learning, computer science or related field
  • Genuine machine learning background able to keep pace with research-driven team
  • Strong Python and PyTorch
  • Experience building concurrent or parallel systems (multiprocessing, async I/O, threading)
  • Hands-on exposure to distributed machine learning via internship, coursework, or projects
  • Experience working with AWS, GCP or other hyperscalers
  • Australia-based (must be located in Australia)
  • Professional-level English proficiency (written and spoken)
  • Comfortable working across timezones and collaborating with a distributed team
  • Top-tier ML publications
  • Open-source contributions to ML frameworks, distributed systems or networking libraries
Am I A Good Fit?
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The Company
15 Employees

What We Do

Pluralis is developing a protocol that facilitates collaborative training and ownership of foundation models.

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