Research Engineer
Engineering5+ yearsRemote · Bangalore, India
Vidman AI operates serverless inference across the major open model families and trains custom models on dedicated GPUs. As a Research Engineer you improve the models themselves — from Vidman AI Adaptive, our automatic router across the model pool, to the fine-tuning methods and alignment recipes customers run. You turn research into behavior that serves production traffic.
What you'll do
- 01Build and evaluate routing strategies for Vidman AI Adaptive (our default routing endpoint) across the open-model pool, and measure what they do to quality, latency, and cost.
- 02Design fine-tuning and alignment recipes — SFT, LoRA/QLoRA, DPO-family objectives, continued pre-training — that behave predictably on dedicated-GPU infrastructure.
- 03Build evaluation harnesses that catch regressions before customers feel them.
- 04Read the literature, reproduce what matters, discard the rest, ship what wins.
- 05Work with product engineering to make research outcomes visible and controllable in product surfaces.
- 06Write down what gets learned — internal notes, docs, occasionally public posts.
What you bring
- At least 5 years in machine learning engineering or research, with meaningful time on large language models.
- Hands-on experience fine-tuning open-weight models — PyTorch, distributed training, parameter-efficient methods.
- Evaluation rigour: when a model is called better, able to show how that is known.
- Engineering fundamentals strong enough for someone else to reproduce the experiments.
Nice to have
- Publications or substantial open-source work in post-training, routing, or evaluation — any one of the three.
- Preference optimisation beyond the basics — DPO variants, reward modeling, online RL.
- Inference-time optimisation: quantization, speculative decoding, serving-stack internals.
- Mixture-of-experts familiarity, hands-on or academic.