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Ekacare

ML Research Engineer - Pre-training (LLMs)

Bengaluru · Mid Level

Older listing - lower visibility likelyVerified listingPosted 56d ago

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Skills required

4 listed
Personal Health RecordsLarge Language Models (LLMs)AWS Elastic MapReduce (EMR)Current Procedural Terminology (CPT)
Personal Health RecordsLarge Language Models (LLMs)AWS Elastic MapReduce (EMR)Current Procedural Terminology (CPT)

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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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Two ways in

Applicants who checked fit first are 3.1× more likely to hear back

Your match scoreCalculated · locked
86Overall
64Skills
97Experience

Your score for this role already exists

ASAI compared this JD against 41 signals - skills, seniority, domain, stack overlap etc. Add a resume and it unlocks in about 30 seconds.

No credit card · 1 tap with Google

Free · no signup

Get tomorrow's jobs before you have to search

Daily job drops, skill trends and free resources - posted straight to the group. Leave any time.

Join WhatsAppJoin Telegram

No spam. Just jobs and resources.

Why people use ASAI

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.

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