This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a AI Researcher — Training Optimization based in India.
This research-focused role offers the prospect to improve the efficiency, stability, and scalability of large-scale AI model training.
You will work at the intersection of machine learning research and systems engineering to develop practical training optimization techniques.
Your work will target areas such as convergence, training cost, memory efficiency, numerical stability, and model quality.
You will design rigorous experiments, analyze large-scale results, and turn research insights into measurable improvements.
The role also provides opportunities to publish research and contribute to the broader machine learning community.
You will collaborate closely with infrastructure and inference teams to ensure research decisions translate effectively into real-world performance.




This is an ideal environment for an independent researcher who enjoys solving challenging problems and turning novel ideas into practical results.
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Accountabilities:
Design, implement, and evaluate novel training optimization techniques for large-scale neural networks, including optimization algorithms, schedulers, normalization methods, and curriculum strategies.
Investigate approaches for improving training efficiency, stability, convergence speed, and overall model quality across long training runs and large datasets.
Research and implement techniques involving optimizer and scheduler innovations, mixed- and low-precision training, memory-efficient training, gradient noise reduction, scaling laws, and convergence analysis.
Explore training-time regularization and robustness techniques that can improve model performance and reliability.
Design and execute large-scale experiments, analyze results rigorously, and translate findings into actionable improvements to training systems and methodologies.
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📌 AI Researcher — Training Optimization (India)
🏢 Jobgether
📍 India