ML Research Engineer - Pre-training (LLMs)
ekacare· Data Science.
About this role
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.
Frequently Asked Questions
Is the salary disclosed for the ML Research Engineer - Pre-training (LLMs) position at ekacare?
The salary for this ML Research Engineer - Pre-training (LLMs) role at ekacare is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the ML Research Engineer - Pre-training (LLMs) position at ekacare located?
This ML Research Engineer - Pre-training (LLMs) role at ekacare is based in Bengaluru, KA, India. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Is the ML Research Engineer - Pre-training (LLMs) role at ekacare full-time or part-time?
This is listed as a FULL TIME position. It is posted as a ML Research Engineer - Pre-training (LLMs) role in the Data Science. department at ekacare.
Which team or department does the ML Research Engineer - Pre-training (LLMs) at ekacare belong to?
This ML Research Engineer - Pre-training (LLMs) position is part of the Data Science. department at ekacare. See the full job description for more information about the team structure and responsibilities.
How do I apply for the ML Research Engineer - Pre-training (LLMs) position at ekacare?
Click the "Apply Now" button on this page. You will be redirected to ekacare's official application portal hosted on keka where you can submit your application directly.
When was the ML Research Engineer - Pre-training (LLMs) job at ekacare posted?
This ML Research Engineer - Pre-training (LLMs) position at ekacare was posted on Aug 10, 2026. Apply as soon as possible — early applications are often reviewed first.
ML Research Engineer - Pre-training (LLMs)
ekacare
You'll be redirected to ekacare's official application page on keka.