Applied AI Researcher

About the company

AI + Quantum Computing

What You'll Do

• Design and build 

  multi‑agent LLM systems

   for complex reasoning workflows
• Design domain specific scaffolds (prompts, datasets) and robust evaluation frameworks to guide AI systems in specialized environments
• Implement reinforcement learning enhancements (RLHF, DPO, GRPO, SFT) for agent optimization
• Fine tune and deploy small reasoning models; perform post‑training domain adaptation
• Engineer scalable training/inference pipelines on multi node GPU clusters with containerized infrastructure
• Collaborate with product and vertical teams to transition research into real world applications
• Contribute to publications, open source work, and internal learning across the company

Who We're Looking For

• MS or PhD in CS, ML, AI or a related technical field
• 4+ years in 

  applied AI research

• Proficient in Python + PyTorch or JAX, including scaled or custom implementations
• Practical experience with RL techniques like RLHF, DPO, GRPO, SFT
• Exposure to chain of thought prompting and dataset creation
• Demonstrated experience building and deploying 

  multi‑agent systems

• Experience with distributed infrastructure: Docker/Kubernetes, Ray, Hydra, MLflow
• Bonus if you have publications (NeurIPS, ICLR, ICML, AAMAS) or domain experience in drug discovery, materials, quantum control, chip design
• Open source contributions to AI research or tooling
• Experience optimizing large scale models for inference and deployment.

What We Offer

• Work on world class AI Quantum systems that push scientific and industrial boundaries
• Access to one of the country's most advanced quantum systems + top tier GPU/HPC infrastructure
• Ownership and flexibility, define your research direction and release real world impact
• Competitive package with performance bonus and ESOPs
• Collaborative, knowledge sharing culture with industry leading experts

If you fit the qualifications and are passionate about pushing the frontier of AI + Quantum, we’d love to hear from you!

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