Staff Research Scientist – Reinforcement Learning

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🕒 July 3

🏄 California – Remote

🏄 California – Remote

💵 $200k - $250k / year

⏰ Full Time

🔴 Lead

🧬 Research Scientist

👻 Ghost score 35%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Centific

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

🤖 Artificial Intelligence

🛍️ eCommerce

🏢 Enterprise

Artificial Intelligence • eCommerce • Enterprise

Centific is a company that provides Zero distance innovation™ solutions for Generative AI (GenAI) creators and industries. The company focuses on rapid, safe, and scalable AI deployment, offering high-quality data and models to drive business impact through accelerated deployments. With expertise in AI and data science, Centific is positioned as a leader in data annotation and labeling for AI/ML, recognized by the Everest Group’s 2024 assessments. Their AI platforms support enterprise-ready applications, particularly improving search, personalization, fraud detection, and customer engagement in ecommerce environments. Centific serves a wide array of industries with foundational and frontier AI data solutions, fostering partnerships with leading model providers to advance sustainable GenAI models and applications.

📋 Description

• Design simulation environments and digital twins for enterprise workflows • Post-train LLM agents using RLHF, DPO, GRPO, PPO, and emerging methods • Build pipelines that convert human-labeled traces and verifiable signals into training data • Architect multi-turn, tool-using agents with closed learning loops • Design reward functions and verifiers that resist reward hacking and reflect real task outcomes • Set the technical bar across the team — architecture, code review, engineering standards • Mentor researchers and engineers; drive technical direction through influence • Translate research into production; contribute to publications

🎯 Requirements

• 7+ years in ML/AI research or engineering; 3+ years at senior/staff level • MS or PhD in Computer Science, Machine Learning, or related field (or equivalent) • 5+ years hands-on RL — environment design, reward engineering, policy optimization — with at least one production deployment LLM Post-Training • 3+ years fine-tuning LLMs with hands-on RL post-training (RLHF, DPO, GRPO, PPO) • Expert-level implementation of RLHF pipelines, reward modeling (Bradley-Terry), DPO, and KTO • Strong Python and software engineering skills — comfortable building production pipelines, not just notebooks • Deep expertise in MDPs, policy gradient methods (PPO, SAC), and temporal difference learning • Working knowledge of modern post-training and rollout-serving libraries (TRL, veRL, OpenRLHF, SkyRL)

🏖️ Benefits

• Health insurance • 401(k) matching • Flexible work hours • Paid time off • Remote work options

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