Senior/Staff Research Scientist - Machine Learning (LLM/Post-Training/GRPO) - Up to $400K + equity - Remote

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

Benefits offered by this job

Equity

Remote work (USA)

Job summary

Attis is seeking a Machine Learning Engineer to build and optimize state-of-the-art LLMs for edge-ready deployments. You will drive post-training, alignment, and model compression across open-weight models, experimenting with quantization, distillation and advanced optimization techniques.

This fully remote role in the United States offers a salary between $250k and $400k plus equity. The ideal candidate has experience distributing training across GPU clusters, serving KV-cache-optimized

Qualifications

• Hands-on experience fine-tuning open-weight models with alignment techniques (GRPO, DPO, RLVR) or model compression methods (Quantization, Distillation, FP8/AWQ).
• Experience training across distributed GPU clusters (16+ H100/B200 nodes) using Slurm, FSDP, or DeepSpeed.
• Expertise in serving, parallel worker rollouts, and KV-cache optimization via vLLM, SGLang, or TensorRT-LLM.
• Exposure to mission-critical applications in Robotics, Tactical Edge AI, Autonomous Systems, or Defense preferred.

Responsibilities

• Develop and optimize end-to-end LLM post-training and alignment workflows.
• Experiment with model adaptation, compression, and evaluation to improve edge deployment.
• Collaborate with cross-functional teams to deploy scalable, secure AI solutions.

Skills

LLM

Reinforcement Learning

Post-Training

Model Compression

Distributed Training

Quantization

vLLM

PyTorch

Tools

Slurm

DeepSpeed

TensorRT-LLM

PyTorch

Job description

Machine Learning Engineer (LLM/RL/Post-Training/DPO/GRPO), Remote, USA (Between $250-400K DOE + equity)

ML Engineers/Research Scientists sought for a well-funded, highly successful frontier AI scaleup who build state of the art models for the tactical edge. They are a talented team of engineers and researchers who perform the full stack of model training to improve models every day. We are seeking true Model Builders - scientists who operate at the PyTorch loss-function and kernel layer to execute the full stack of open-weight LLM post-training, alignment, and model compression every single day.

The company is developing advanced AI systems that can operate directly at the edge, bringing high-performance AI into demanding real-world environments without relying on constant cloud connectivity. Its technology enables sophisticated models to run securely across laptops, embedded devices, robotic platforms and other hardware, with models optimized for specific applications and operational requirements.

Offering a base of between 250-400K depending on experience + generous equity, fully remote working in the US and other benefits.

Ideally you will have experience performing experimentation in one or more of the following areas:

• Post-Training & Alignment: Hands-on experience adapting or fine-tuning open-weight models (Qwen, Llama, DeepSeek) using modern alignment techniques (GRPO, DPO, RLVR) OR model compression methods (Quantization, Distillation, FP8/AWQ) instead.
• Cluster Scale Compute: Experience training models across distributed GPU clusters (16+ H100/B200 nodes) using Slurm, FSDP, or DeepSpeed.
• Rollout Mechanics: Expertise in serving, parallel worker rollouts, and KV-cache optimization via vLLM, SGLang, or TensorRT-LLM.
• Domain Alignment (Preferred but NOT essential): Prior exposure to mission-critical applications across Robotics, Tactical Edge AI, Autonomous Systems, or Defense (US Space Force, DoD, DARPA, JHU APL, Sandia).

We have a strong preference for candidates with an active clearance to work on projects related to US Space Force, DoW, DoD etc.

Key Skills

Large Language Models, LLM, Foundation Models, Generative AI, Reinforcement Learning, RLHF, Reinforcement Learning from Human Feedback, Post-Training, Pretraining, Midtraining, Fine-Tuning, Model Adaptation, Model Training, Distributed Training, Multimodal, Vision-Language Models, VLM, Vision Model Training, Machine Translation, Multilingual Models, Model Evaluation, LLM Evaluation, Benchmarking, Benchmark Development, Data Ablation, Model Distillation, Quantization, Model Compression, Robotics + LLM, Edge AI

Disclaimer

Attis Global Ltd is an equal opportunities employer. No terminology in this advert is intended to discriminate on any of the grounds protected by law, and all qualified applicants will receive consideration for employment without regard to age, sex, race, national origin, religion or belief, disability, pregnancy and maternity, marital status, political affiliation, socio-economic status, sexual orientation, gender, gender identity and expression, and/or gender reassignment. M/F/D/V. We operate as a staffing agency and employment business. More information can be found at attisglobal.com.