United States onlyAbout 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’sPhysical AI team is building next-generation AI systems at the intersection ofVision AI, multimodal foundation models, agentic AI, simulation, and real-world robotics. We work on practical and frontier problems spanning video understanding, autonomous systems, embodied intelligence, data pipelines, evaluation, and deployment.
We are looking for anAI Engineerwho 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 asperception, dexterity, navigation, simulation, and autonomous decision-making.
Key Responsibilities
Design, build, and deploy AI/ML systems acrossVision AI, multimodal AI, agentic AI, and Physical AIuse cases.
Develop and integrate models forvideo understanding, imageperception, tracking, multimodal reasoning, autonomous workflows, and robotics-related tasks.
Work with research and engineering teams toproductionizemodels using platforms such asNVIDIA NeMo, Riva, RAPIDS, Triton, Isaac stack, AWS Bedrock, GCP Vertex AI, and related SDKs.
Build pipelines forlarge-scale structured and unstructured data, including video, audio, sensor, and text data.
Implement andoptimizemodel inference, evaluation, monitoring, drift detection, and governance workflows in production environments.
Support experimentation withLLMs, VLMs, world models, agent frameworks, tool-using agents, and memory-enabled agentic systems.
Contribute to AI systems forsimulation, digital twins, roboticsperception, dexterous manipulation, long-horizon task execution, autonomous driving, and edge-case evaluation.
Perform data analysis, error analysis, benchmarking, and model improvement for robustness, safety, and generalization.
Collaborate directly with customers and internal teams toidentifyrelevant datasets, define success metrics, and translate business needs into AI system design.
Help build reusable internal frameworks, accelerators, and data products for multimodal and agentic AI deployments.
Qualifications
Master’s degree inComputerScience, MachineLearning, or equivalent practical experience.
5+ years of experience building and deploying large scale AI/ML systems in production.
Strong programming skills inPythonand solid experience with modern ML frameworks such asPyTorch, TensorFlow, or JAX.
Hands-on experience withVision AI, including one or more of: image/video models, object detection, tracking, segmentation, grounding, video analytics, 3D vision, or multimodal perception.
Experience withGenerative AI, includingLLMs, VLMs, multimodal pipelines, RAG, agents, or agent orchestration frameworks.
Familiarity withagentic AIconcepts such as tool use, planning, workflow orchestration, and memory; experience withagentic memory or knowledge-graph-backed agentsis a plus.
Experience working with NVIDIA AI ecosystem tools such asNeMo, RAPIDS, Riva, Triton, andideallyexposure toIsaac Sim / Omniverseor related simulation environments.
Experience building scalable inference or training pipelines onGPU infrastructure, with familiarity in performance optimization, distributed systems, or high-performance networking.
Ability to design experiments, evaluate hypotheses, and implement optimization workflows for real-world AI systems.
Strong communicationskills and ability to work directly with customers, researchers, and cross-functional engineering teams.
Preferred Qualifications
Experience withrobotics, autonomous driving, simulation, digital twins, or embodied AI systems.
Familiarity withRay, Kubernetes, Docker,FastAPI, TensorRT, MLflow/W&B, or related MLOps and distributed AI tooling.
Exposure tosensor fusion, audio/video analytics, multimodal data pipelines, orroboticsdata formats.
Experience with model governance, observability, safety evaluation, or production model monitoring.
Comfort working across both applied engineering and research-driven prototyping.
Why Join Us
Work on frontier problems inVision AI, agentic AI, and Physical AI.
Build systems that connectresearch-grade models to real deployments.
Collaborate with a strong cross-functional team spanning engineering, data science, simulation, and robotics.
Help shape the next generation of AI systems for real-world action.
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