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Job description

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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Alerts as often as hourly. Reach new roles while the pile is still small.

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Verified jobs, only. Say no to ghost jobs. Your time deserves respect.

Someone shared one job with you. ASAI keeps finding the rest.

Scored, not searched. Every role ranked against your actual profile.

Alerts as often as hourly. Reach new roles while the pile is still small.

Skill gaps, spelled out. See exactly which requirements you don't meet yet.

Verified jobs, only. Say no to ghost jobs. Your time deserves respect.

ML Research Engineer - Pre-training (LLMs)

What we know about this role

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Job description

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Someone shared one job with you. ASAI keeps finding the rest.