Full-Time

Staff Research Scientist

Reinforcement Learning

Updated on 9/3/2026

Centific

Centific

1,001-5,000 employees

Data-driven AI solutions for business growth

Compensation Overview

$200k - $250k/yr

Remote in USA

Remote

Master's, PhD

Category
AI & Machine Learning (1)
Required Skills
LLM
Python
Reinforcement Learning

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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
  • 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
  • Working knowledge of modern post-training and rollout-serving libraries (TRL, veRL, OpenRLHF, SkyRL)
  • Experience building LLM-based agents: tool use, multi-turn reasoning, trajectory evaluation
  • 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
  • Hands-on experience with Gymnasium-based environments and reward engineering (sparse vs. dense)
Responsibilities
  • 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
Desired Qualifications
  • Publications at NeurIPS, ICML, ICLR, ACL, COLM, or similar venues
  • Open-source contributions to post-training or agent frameworks (TRL, veRL, OpenRLHF, SkyRL)
  • Experience with Offline RL (CQL, IQL), Model-based RL / World Models, or Hierarchical RL
  • Background in synthetic data generation, simulation, or world models
  • Domain experience in healthcare, finance, logistics, or compliance
  • Distributed training on GPU clusters

Centific delivers data and AI-enabled, human-centered solutions to help brands solve complex business challenges. Its offerings span Generative AI, data collection, curation and annotation, localization, digital fraud and safety, and growth marketing. The company operates by combining data gathering and cleaning with AI models, localized adaptations, and safety controls to drive smarter decisions and growth, often incorporating human-in-the-loop processes for quality. Centific differentiates itself through more than two decades of Data and AI experience, a clear vision, operational excellence, and a focus on sustainable, long-term value and loyal customers. Its goal is to help brands thrive in a sustainable and meaningful way by enabling smarter operations and meaningful customer relationships.

Company Size

1,001-5,000

Company Stage

Series A

Total Funding

$60M

Headquarters

Redmond, Washington

Founded

2020

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Simplify Jobs

Simplify's Take

What believers are saying

  • Premier’s January 2025 chatbot agreement opens healthcare distribution and paid enterprise references.
  • NVIDIA Cosmos 3 and Cosmos 3 Edge collaborations in 2026 validate Centific’s physical AI relevance.
  • Data Marketplace governance upgrades in April 2026 target repeatable enterprise revenue and easier onboarding.

What critics are saying

  • NVIDIA dependency concentrates differentiation; a partner pivot would blunt Centific’s 2026 product narrative.
  • Enterprise AI services face brutal competition from Scale AI, Appen, and hyperscalers by 2026.
  • Leadership transition in August 2026 after rapid product launches signals execution risk and potential founder disruption.

What makes Centific unique

  • June 2025 $60M Series A from Granite Asia funds Centific’s AI data backbone expansion.
  • Centific pairs data annotation, localization, and AI workflows across cloud, edge, and on-prem.
  • 2026 launches span VerityAI SLiM, Data Canvas, and RL Environments-as-a-Service for physical AI.

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Benefits

Flexible Work Hours

Remote Work Options

Hybrid Work Options

Growth & Insights and Company News

Headcount

6 month growth

3%

1 year growth

3%

2 year growth

6%
TechAnnouncer
Oct 16th, 2025
Centific Inc. secures $60M for AI.

In 2025, AI startups are booming, with new companies offering specialized solutions like bug-fixing software and AI marketing agents. Significant funding rounds are fueling growth, with enterprise AI platforms, retail tech, and AI governance solutions attracting major investments. Notable funding includes Centific Inc. securing $60 million and Augmodo raising $37 million. The focus is on practical AI applications across diverse sectors, highlighting AI's foundational role in the innovation economy.

PR Newswire
Jun 25th, 2025
Centific, the Market-Leading Enabler of Advanced AI, Closes Transformative $60M Series A Round

/PRNewswire/ -- Centific, the AI Data Foundry trusted by the world's top model builders, AI labs, and enterprise innovators, today announced the close of its...

FinSMEs
Jun 25th, 2025
Centific Closes $60M Series A Funding Round

Centific, a Seattle, WA-based AI data foundry, raised $60M in Series A funding.

CanadianSME Small Business Magazine
Jun 25th, 2025
Centific, the Market-Leading Enabler of Advanced AI, Closes Transformative $60M Series A Round

Centific closes $60M Series A, led by Granite Asia, to fuel data needs for next wave of agentic AIPost this

Biharprabha
Jun 25th, 2025
Centific Secures $60M Series A Funding

Centific, an AI data enabler, secured a $60 million Series A funding round led by Jenny Lee of Granite Asia. The investment will fuel Centific's expansion as a key player in AI infrastructure, supporting the development and deployment of advanced AI systems. The company aims to enhance its platform, boost R&D, and strengthen alliances with tech giants like NVIDIA and Microsoft, positioning itself as a foundational partner for enterprise AI deployments.