Remote Research Scientist: Edge AI & LLM Mastery | Equity

Attis; United States; Remote; USD 250,000 - 400,000; Full time

Benefits offered by this job

Equity

Remote in USA

Competitive salary

Job summary

Attis is seeking a Research Scientist (LLM/RL/Post-Training/DPO/GRPO) to advance edge AI at scale, remotely from the USA. You will work on open-weight model post-training, alignment, and model compression across end‑to‑end pipelines, collaborating with engineers and researchers to push state-of-the-art capabilities.

Ideal candidates have hands-on experience with distributed GPU clusters, PyTorch loss‑function optimization, and KV‑cache tuning for fast inference.

Qualifications

• Hands-on experience fine-tuning open-weight models using alignment techniques (GRPO, DPO, RLVR) or model compression methods.
• Experience training models across distributed GPU clusters (16+ H100/B200) with Slurm, DeepSpeed, or FSDP.
• Proven ability to optimize serving, rollouts and KV-cache with vLLM, SGLang, or TensorRT‑LLM.
• Preference for candidates with clearance related to US Space Force/DoD programs.

Skills

LLMs

Reinforcement Learning

RLHF

Post-Training

Model Compression

Quantization

Distillation

Distributed Training

Edge AI

Tools

Slurm

DeepSpeed

FSDP

vLLM

TensorRT-LLM

Job description

Attis is seeking a Research Scientist (LLM/RL/Post-Training/DPO/GRPO) to advance edge AI at scale, remotely from the USA. You will work on open-weight model post-training, alignment, and model compression across end‑to‑end pipelines, collaborating with engineers and researchers to push state-of-the-art capabilities.

Ideal candidates have hands-on experience with distributed GPU clusters, PyTorch loss‑function optimization, and KV‑cache tuning for fast inference.