Research Engineer – Generative AI (LLMs)

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!