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Open nowPosted 73 days ago

ML Research Engineer - Pre-training (LLMs)

Eka.care26 open roles

Where
Bengaluru
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Your applicationOpen nowML Research Engineer - Pre-training (LLMs)Eka.care · Bengaluru

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This job: posted 73 days ago

The posting

ML Research Engineer; Pre-training (LLMs)

Bengaluru · Full-time · Experience: 2–4 yrs

About EkaCare and the mission

EkaCare is India's connected healthcare platform: an EMR that doctors run their practices on, a personal health record used by millions of Indians, and one of the deepest integrations with India's ABDM digital-health rails. Our Parrotlet family of medical models already serves Indian doctors in production, and we open-source our work where it counts.

The role

The recipe is the game. You'll work at the heart of the 30B CPT: what goes into the ~500B-token mix, in what order, at what scale, proven cheaply at proxy scale, then spent confidently on the big run.

What you'll do

  • Design and run CPT/mid-training ablation ladders at proxy scale, the experimental backbone that decides the real run.
  • Own data-mix and curriculum empirics: medical vs general, Indic vs English, replay ratios (~70% design point), annealing schedules.
  • Debug training at scale: loss spikes, precision issues, dataloader stalls, checkpoint pathologies.
  • Build per-stage eval hooks so every CPT phase has a scoreboard, not a vibe.
  • Run tokeniser, long-context and MoE-health experiments (routing balance, expert utilisation).

What we look for

  • 2–4 years in ML with pretraining or CPT you personally ran at ≥1B scale (ideally ≥7B, 100B+ tokens) — the recipe was yours to break and fix.
  • Fluency with Megatron/NeMo/TorchTitan-class trainers and distributed fundamentals (TP/PP/DP, mixed precision).
  • Empirical rigour: you design ablations that answer questions.
  • You read papers fast and implement faster.

Bonus

  • MoE training exposure; scaling-laws mindset.
  • Indic-language or domain-specific (medical/legal/code) pretraining.
  • Kernels curiosity — you've opened a profiler and enjoyed it.

Why this is a rare gig

  • Open source, with your name on it: weights and technical reports ship publicly.
  • India-scale mission: models for a billion people in their own languages.
  • Compute that’s rare to fine: dedicated multi-node H200 training under a national grant.
  • Small senior team: you work with the people who own the recipe.
  • A live deployment path: Government institutes, EkaCare's doctors and patients use what you ship.
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