4 months ago
Remote, United StatesMid Level
Base Salary
$150k - $300k/yr
Responsibilities
- Design and build custom RL environments and digital twins that simulate complex enterprise workflows.
- Post-train LLM-based agents on domain-specific tasks using PPO, GRPO, DPO, RLHF, and related methods.
- Build end-to-end pipelines that convert human-labeled traces into RL training data.
- Architect multi-step reasoning agents with tool-calling and closed learning loops.
- Design reward functions, programmatic verifiers, and validation frameworks for pre-deployment testing.
- Translate RL research into scalable production systems and contribute to publications.
- Help shape product direction and make governed RL accessible to enterprise customers.
Requirements
- At least 3 years of hands-on experience with RL environment design, reward engineering, and policy optimization.
- Experience fine-tuning LLMs using RLHF, DPO, PPO, or similar techniques.
- Production software engineering experience beyond research, including scalable pipelines and training infrastructure.
- Experience with LLM-based agents, tool use, and multi-step reasoning.
- Strong Python skills and experience with Gymnasium, RLlib, Stable Baselines, and PyTorch, JAX, or TensorFlow.
- MS or PhD in computer science, machine learning, or a related field, or equivalent experience.
- Preferred: publications at NeurIPS, ICML, ICLR, ACL, or similar venues.
- Preferred: enterprise workflow experience in healthcare, finance, logistics, or compliance.
- Preferred: open-source contributions to CleanRL, TRL, veRL, or agent frameworks.
- Preferred: experience with world models, synthetic data generation, simulation, distributed training, and large-scale RL experimentation.
Benefits
- Hybrid/remote work arrangement in Palo Alto, California or Seattle, Washington.
- Opportunity to shape a new discipline at the intersection of reinforcement learning, simulation, and enterprise AI.
- Opportunity to apply research to real systems across healthcare, finance, and safety.
- Collaboration with NVIDIA, Microsoft, and the global AI community.
Categories
AI ResearchML Engineering
About Centific
Centific builds AI data and engineering platforms and services for enterprises, including curated multimodal datasets, industry‑tuned LLMs, and RAG pipelines backed by vector databases. It monetizes through software, data operations, and consulting to design, deploy, and scale GenAI systems, along with QA automation and digital engineering work. Privately held and headquartered in Redmond, Washington, the company raised a $60M Series A in 2025 to expand its AI data foundry and platform capabilities.