Principal AI Research Scientist

Job not on LinkedIn

🕒 September 1

🏄 California, Washington – Remote

🏄 California – Remote ☕ Washington – Remote

💵 $200k - $300k / year

⏰ Full Time

🔴 Lead

🧠 AI Research Scientist

👻 Ghost score 33%

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

• Define and drive Centific’s research agenda in Vision AI, multimodal foundation models, simulation-first learning, agentic AI, and embodied intelligence • Lead high-impact research in multimodal foundation models, world models, embodied AI, vision-language-action systems, and agentic AI • Develop approaches for perception, temporal reasoning, spatial intelligence, affordance understanding, autonomous decision-making, and sim2real transfer • Advance robotics capabilities including dexterous manipulation, contact-rich interaction, bimanual coordination, long-horizon task execution, navigation in dynamic environments, and robust action under uncertainty • Contribute to multimodal pretraining, distributed training, fine-tuning, distillation, and model evaluation • Shape research relevant to autonomous driving and mobile autonomy • Guide integration with simulation and digital twin platforms such as Isaac Sim, Isaac Lab, MuJoCo, and Omniverse • Establish benchmarks and reproducible evaluation frameworks for robustness, safety, generalization, manipulation success, policy performance, and deployment readiness • Lead a small team of researchers, engineers, and interns • Mentor Ph.D. interns and engineers and help build a rigorous research culture

🎯 Requirements

• Ph.D. in Computer Science, Robotics, Machine Learning, Computer Vision, Autonomous Systems, or a related field • Strong publication record in top venues such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, CoRL, RSS, or leading autonomous driving/robotics venues • 5+ years of research experience in academia, industry, or advanced R&D environments • Demonstrated experience building or advancing large-scale foundational models, novel architectures, or training methods in multimodal AI, vision, robotics, autonomous driving, embodied AI, world models, or simulation-based learning • Deep expertise in PyTorch and/or JAX, GPU training, distributed experimentation, and large-scale model development • Proven ability to lead ambitious technical programs and mentor junior researchers • Publications or patents in multimodal foundation models, dexterous robotics, autonomous driving, spatial intelligence, simulation-based learning, manipulation, or embodied AI • Strong experience in Vision AI, including perception, tracking, grounding, 3D scene understanding, video understanding, sensor fusion, or multimodal reasoning • Familiarity with agentic AI systems, tool-using agents, planning frameworks, and memory-based architectures; experience with agentic memory, knowledge graphs, or long-horizon reasoning systems is a plus • Experience with Isaac Sim, MuJoCo, OpenUSD/Omniverse, Open3D, PyTorch3D, NeRF/3DGS, or related simulation and 3D stacks • Familiarity with imitation learning, reinforcement learning, planning, MPC, control, teleoperation data pipelines, or policy learning for robotics and autonomous systems • Experience with Ray, Kubernetes, Triton, TensorRT, Docker, W&B, or large-scale training and deployment infrastructure • Background in trustworthy AI, robotics safety, evaluation, or explainability for autonomous systems

🏖️ Benefits

• Opportunity to publish frontier work • Mentorship and research leadership opportunities • Opportunity to see research move into real systems • Equal-opportunity employment

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