Research Engineer – Generative AI (LLMs)

Research Engineer – Generative AI (LLMs)

Location:

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!