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 highperformance 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: Strong 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!