Job description

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 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 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 , dexterity, navigation, simulation, and autonomous decision-making. Key Responsibilities Design, build, and deploy AI/ML systems across Vision AI, multimodal AI, agentic AI, and Physical AI use cases. Develop and integrate 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 systems . Contribute to AI systems for simulation, digital twins, robotics perception , 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 to identify relevant 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 in Computer Science , Machine Learning , or equivalent practical experience. 5 years of experience building and deploying large scale AI/ML systems in production. Strong programming skills in Python and solid experience with modern ML frameworks such as PyTorch , TensorFlow, or JAX. Hands-on experience with Vision AI , including one or more of: image/video models, object detection, tracking, segmentation, grounding, video analytics, 3D vision, or multimodal perception. Experience with Generative AI , including LLMs, VLMs, multimodal pipelines, RAG, agents, or agent orchestration frameworks . Familiarity with agentic AI concepts such as tool use, planning, workflow orchestration, and memory; experience with agentic memory or knowledge-graph-backed agents is a plus. Experience working with NVIDIA AI ecosystem tools such as NeMo, RAPIDS, Riva, Triton , and ideally exposure to Isaac Sim / Omniverse or related simulation environments. Experience building scalable inference or training pipelines on GPU 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 communication skills and ability to work directly with customers, researchers, and cross-functional engineering teams. Preferred Qualifications Experience with robotics, autonomous driving, simulation, digital twins, or embodied AI systems . Familiarity with Ray, Kubernetes, Docker, FastAPI , TensorRT, MLflow/W&B , or related MLOps and distributed AI tooling. Exposure to sensor fusion, audio/video analytics, multimodal data pipelines, or robotics data 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 in Vision AI, agentic AI, and Physical AI . Build systems that connect research-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. Salary: $160,000-$220,000 OTB Centific is an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, citizenship status, age, mental or physical disability, medical condition, sex (including pregnancy), gender identity or expression, sexual orientation, marital status, familial status, veteran status, or any other characteristic protected by applicable law. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.

Requirements

Must-haves

Design, build, and deploy AI/ML systems across Vision AI, multimodal AI, agentic AI, and Physical AI use cases.
Develop and integrate 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 systems .
Contribute to AI systems for simulation, digital twins, robotics perception , 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 to identify relevant 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.
Master’s degree in Computer Science , Machine Learning , or equivalent practical experience.
5 years of experience building and deploying large scale AI/ML systems in production.
Strong programming skills in Python and solid experience with modern ML frameworks such as PyTorch , TensorFlow, or JAX.
Hands-on experience with Vision AI , including one or more of: image/video models, object detection, tracking, segmentation, grounding, video analytics, 3D vision, or multimodal perception.
Experience with Generative AI , including LLMs, VLMs, multimodal pipelines, RAG, agents, or agent orchestration frameworks .
Experience working with NVIDIA AI ecosystem tools such as NeMo, RAPIDS, Riva, Triton , and ideally exposure to Isaac Sim / Omniverse or related simulation environments.
Experience building scalable inference or training pipelines on GPU 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.

Nice-to-haves

Familiarity with agentic AI concepts such as tool use, planning, workflow orchestration, and memory; experience with agentic memory or knowledge-graph-backed agents is a plus.
Experience with robotics, autonomous driving, simulation, digital twins, or embodied AI systems .
Familiarity with Ray, Kubernetes, Docker, FastAPI , TensorRT, MLflow/W&B , or related MLOps and distributed AI tooling.
Exposure to sensor fusion, audio/video analytics, multimodal data pipelines, or robotics data formats .
Experience with model governance, observability, safety evaluation, or production model monitoring.
Comfort working across both applied engineering and research-driven prototyping.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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Platform: workday
Effort: long

Benefits

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