AI Research Engineer: Vision AI / VLM / Physical AI

Centific

2d • $140,000 - $150,000 • Remote

About The Position

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 Research Engineer: Vision AI / VLM / Physical AI Company: Centific Location: Seattle, WA (or Remote) Type: Full‑time Build the Future of Perception & Embodied Intelligence Are you pushing the frontier of computer vision, multimodal large models, and embodied/physical AI—and have the publications to show it? Join us to translate cutting-edge‑ research into production systems that perceive, reason, and act in the real world. The Mission We are building state of‑ t‑heart Vision AI across 2D/3D perception, egocentric/360° understanding, and multimodal reasoning. As an AI Research Engineer, you will own high‑ ‑leverage experiments from paper → prototype → deployable module in our platform. We are seeking passionate Engineersto join our cutting-edge labs, you could be part of : Computer Vision team as a Research Engineer and dive into the world of 3D reconstruction, scene understanding, and visual AI. You’ll explore innovative techniques like those used to transform real-world spaces into immersive 3D models—such as the 3D Reconstruction projects —and work with cutting-edge architectures like VGG-T (Visual Geometry Grounded Transformers), known for advancing deep learning in vision tasks. This role is perfect for those excited to develop AI systems that interpret, reconstruct, and interact with the visual world, using state-of-the-art tools and methodologies. Physical AI Robotics team, where you’ll work at the intersection of simulation, robotics, and AI. You’ll leverage NVIDIA’s Omniverse for advanced 3D simulation and collaboration, Isaac Sim for robotics training and testing, and GR00T for foundation models in robotics. Experience with Holoscan SDK for real-time medical and industrial robotics pipelines, Newton Physics for dynamic simulation, and NVIDIA’s NERD for neural robot dynamics will be a plus. This role is ideal for those eager to push the boundaries of AI-driven robotics using state-of-the-art tools and frameworks.

Requirements

• Masters/Ph.D in CS/EE/Robotics (or related), actively publishing in CV/ML/Robotics (e.g., CVPR/ICCV/ECCV, NeurIPS/ICML/ICLR, CoRL/RSS).
• Strong PyTorch (or JAX) and Python; comfort with CUDA profiling and mixed precision‑ training.
• Demonstrated research in computer vision and at least one of: VLMs (e.g., LLaVA style, video‑ language‑ models), embodied/physical AI, 3D perception.
• Proven ability to move from paper → code → ablation → result with rigorous experiment tracking.

Nice To Haves

• Experience with video models (e.g., TimeSFormer/MViT/VideoMAE), diffusion or 3D GS/NeRF pipelines, or SLAM/scene reconstruction.
• Prior work on multimodal grounding (referring expressions, spatial language, affordances) or temporal reasoning.
• Familiarity with ROS2, DeepStream/TAO, or edge inference optimizations (TensorRT, ONNX).
• Scalable training: Ray, distributed data loaders, sharded checkpoints.
• Strong software craft: testing, linting, profiling, containers, and reproducibility.
• Public code artifacts (GitHub) and first‑author publications or strong open source‑ impact.

Responsibilities

• Advance Visual Perception: Build and fine‑tune models for detection, tracking, segmentation (2D/3D), pose & activity recognition, and scene understanding (incl. 360° and multi‑view).
• Multimodal Reasoning with VLMs: Train/evaluate vision–language models (VLMs) for grounding, dense captioning, temporal QA, and tooluse; design retrieval‑ augmented and agentic loops for perception‑ action‑ tasks.
• Physical AI & Embodiment: Prototype perception‑in‑the‑loop policies that close the gap from pixels to actions (simulation + real data). Integrate with planners and task graphs for manipulation, navigation, or safety workflows.
• Data & Evaluation at Scale: Curate datasets, author high‑signal evaluation protocols/KPIs, and run ablations that make results irreproducible impossible.
• Systems & Deployment: Package research into reliable services on a modern stack (Kubernetes, Docker, Ray, FastAPI), with profiling, telemetry, and CI for reproducible science.
• Agentic Workflows: Orchestrate multi-agent pipelines (e.g., ‑LangGraphstyle graphs) that combine perception, reasoning, simulation, and ‑codeg eneration to ‑selfc heck and ‑selfcorrect‑.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 101-250 employees