Research Engineer – Generative AI (LLMs)
Location : Remote
Abacus.AI is a leading Generative AI company 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
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.If this sounds exciting, I’d love to connect with you. Please feel free to reply with your updated resume at 📧 megha@abacus.ai.
Looking forward to hearing from you!