Machine Learning Engineer – Intern

Job Description

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.

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.

Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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