Senior Applied Reinforcement Learning Engineer

🕒 June 12

🏄 California, Washington – Remote

🏄 California – Remote ☕ Washington – Remote

💵 $150k - $300k / year

⏰ Full Time

🟠 Senior

👷🏻‍♀️ Engineer

👻 Ghost score 45%

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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 and build custom RL environments (digital twins) simulating enterprise workflows such as document processing, compliance, onboarding, and support automation • Post-train LLM-based agents on domain-specific tasks using PPO, GRPO, DPO, and RLHF • Build end-to-end pipelines converting human-labeled traces into RL training data • Architect multi-step reasoning agents with tool-calling and closed learning loops • Design reward functions, verifiers, and validation frameworks for pre-deployment testing • Translate cutting-edge RL research into production systems • Contribute to publications

🎯 Requirements

• 3+ years hands-on experience with environment design, reward engineering, and policy optimization • Experience fine-tuning LLMs using RLHF, DPO, PPO, or similar • Software engineering experience beyond research with scalable pipelines and training infrastructure • Experience with LLM-based agents, tool use, and multi-step reasoning • Strong Python skills • Experience with Gymnasium, RLlib, and Stable Baselines • Experience with PyTorch, JAX, or TensorFlow • MS/PhD in CS, ML, or related field (or equivalent experience) • 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, and simulation preferred • Distributed training and large-scale RL experimentation preferred

🏖️ Benefits

• Opportunity to lead a new discipline at the intersection of RL, simulation, and enterprise AI • Opportunity to see research power real systems across healthcare, finance, and safety • Collaboration with NVIDIA, Microsoft, and the global AI community • Opportunity to create governed, compliant AI systems enterprises can trust

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