Research Engineer – Generative AI (Dindigul)

Company Description: Abacus.AI is an AGI control center from where you can create, deploy, and monitor AI agents. We offer an AI super assistant for enterprises and professionals.

Role Description: We are building a future where AI assists and automates most work and business processes for enterprises and professionals. We are looking for a Research Engineer to help design, train, and optimize large language models and high‑performance inference systems.

What you’ll do:
- Build and optimize LLM training and inference pipelines on cloud GPUs.
- Generate, curate, and maintain datasets for pretraining and finetuning.
- Implement and improve transformer architectures (attention, positional encodings, MoE).
- Optimize inference using FlashAttention, PagedAttention, KV caches, and serving frameworks like vLLM / sglang.
- Collaborate with research and product teams to design experiments, analyze results, and ship improvements.

What we’re looking for:
- Robust Python skills and solid software engineering practices.
- Hands-on experience with LLM training and inference.
- Proficiency with PyTorch or JAX.
- Experience with Hugging Face libraries: transformers, trl, accelerate.
- Experience training on cloud-hosted GPUs and with distributed / mixed-precision training.
- Strong understanding of transformer internals: attention, positional encodings, MoE.
- Familiarity with writing prompts, tool definitions, and managing context for LLMs in real applications (langchain, pydantic, smolagents).

Nice to have:
- RL for LLMs (RLHF, PPO, GRPO).
- CUDA / GPU kernel or systems-level performance work.
- Experience with training infrastructure: monitoring, checkpointing, networking / distributed systems.

We believe in rewarding top-tier talent directly:
- Premium Compensation Package: up to 1 crore Base and up to 1 Cr Performance Bonus

Looking forward to hearing from you Apply on Kit Job: kitjob.in/job/4luf0p