Senior AI Engineer

About Centific Centific is a frontier AI data foundry that curates diverse, high-quality data, using our purpose-built technology platforms to empower the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. Our team includes more than 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. We harness the power of an integrated solution ecosystem—comprising industry-leading partnerships and 1.8 million vertical domain experts in more than 230 markets—to create contextual, multilingual, pre-trained datasets; fine-tuned, industry-specific LLMs; and RAG pipelines supported by vector databases. Our zero-distance innovation™ solutions for GenAI can reduce GenAI costs by up to 80% and bring solutions to market 50% faster. Our mission is to bridge the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers. We aim to help these organizations unlock significant business value by deploying GenAI at scale, helping to ensure they stay at the forefront of technological advancement and maintain a competitive edge in their respective markets. About Job AI Engineer – Vision AI, Agentic Systems & Physical AI Location: Seattle / Palo Alto / Remote Job Description Centific’s Physical AI team is building next-generation AI systems at the intersection of Vision [... source excerpt omitted ...] spanning video understanding, autonomous systems, embodied intelligence, data pipelines, evaluation, and deployment. We are looking for an AI Engineer who can bridge research and production: someone who can build, fine-tune, evaluate, and deploy AI systems across vision, language, video, simulation, and agentic workflows. You will work closely with research, data science, and platform engineering teams to turn advanced AI ideas into scalable, customer-ready systems. This role is ideal for an engineer with strong hands-on experience in modern AI/ML systems, a solid grasp of multimodal and agentic architectures, and an interest in Physical AI challenges such as perception, dexterit [... source excerpt omitted ...] te models for video understanding, image perception, tracking, multimodal reasoning, autonomous workflows, and robotics-related tasks. Work with research and engineering teams to productionize models using platforms such as NVIDIA NeMo, Riva, RAPIDS, Triton, Isaac stack, AWS Bedrock, GCP Vertex AI, and related SDKs. Build pipelines for large-scale structured and unstructured data, including video, audio, sensor, and text data. Implement and optimize model inference, evaluation, monitoring, drift detection, and governance workflows in production environments. Support experimentation with LLMs, VLMs, world models, agent frameworks, tool-using agents, and memory-enabled agentic sy