AI Research Engineer: Vision AI / VLM / Physical AI

Title: AI Research Engineer: Vision AI / VLM / Physical AI

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.

Job Description

We are seeking passionate Engineers to 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.

What You’ll Do

• 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‑.

Example Problems You Might Tackle

• Long horizon‑ video understanding (events, activities, causality) from egocentric or 360° video.

• 3D scene grounding: linking language queries to objects, affordances, and trajectories.

• Fast, privacy preserving perception for ‑ondevice‑ or edge inference.

• Robust multi‑modal evaluation: temporal consistency, open‑set detection, uncertainty.

• Vision conditioned‑ policy evaluation in sim (Isaac/MuJoCo) with sim2real stress tests.

Minimum Qualifications

• 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.

Preferred Qualifications

• 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.

Our Stack (you’ll touch a subset)

• Modeling:

  PyTorch, torchvision/lightning, Hugging Face, OpenMMLab, xFormers

• Perception:

  YOLO/Detectron/MMDet, SAM/Mask2Former, CLIP‑style backbones, optical flow

• VLM / LLM:

  Vision encoders + LLMs, RAG for video, toolformer‑/agent loops

• 3D / Sim:

  Open3D, PyTorch3D, Isaac/MuJoCo, COLMAP/SLAM, NeRF/3DGS

• Systems:

  Python, FastAPI, Ray, Kubernetes, Docker, Triton/TensorRT, Weights & Biases

• Pipelines:

  LangGraph‑like orchestration, data versioning, artifact stores

Benefits:

• Comprehensive healthcare, dental, and vision coverage

• 401k plan

• Paid time off (PTO)

• And more!

Company Overview:

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.

Learn more about us at centific.com.

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.