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3D Ai Engineer Jobs (NOW HIRING)

Autzu

Senior Physical AI Engineer

San Francisco, CA · On-site

$123K - $169K/yr

We're looking for a Senior Physical AI Engineer to build the simulation, digital twin, perception ... Build 3D understanding, localization, and pose-estimation capabilities * Train and evaluate robot ...

New

Trunk Tools

Senior AI Engineer

Redmond, WA · On-site +1

$117K - $160K/yr

About Job AI Engineer - Vision AI, Agentic Systems & Physical AI Location: Seattle / Palo Alto ... 3D vision, or multimodal perception. * Experience with Generative AI , including LLMs, VLMs ...

Figure

Helix AI Engineer, Generative AI

San Jose, CA · On-site

They are seeking a Helix AI Engineer, Generative AI to build and scale generative models that ... 3D, video prediction, or world models • Prior work in robotics, embodied AI, or real-world ML ...

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How much do 3d ai engineer jobs pay per year?

As of Sep 15, 2026, the average yearly pay for 3d ai engineer in the United States is $145,359.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,000.00 and $173,000.00 per year, depending on experience, location, and employer.

What is a 3D AI engineer?

3D AI Engineers are professionals who combine expertise in artificial intelligence (AI) and three-dimensional (3D) technologies to develop intelligent systems for 3D environments. They work on projects such as creating AI-driven 3D simulations, enhancing computer graphics with machine learning, and developing applications like virtual reality, gaming, or digital twins. Their work often involves programming, 3D modeling, data analysis, and deploying AI algorithms to solve spatial or visual problems within 3D spaces.

What are the key skills and qualifications needed to thrive as a 3D AI engineer?

To thrive as a 3D AI Engineer, you need strong expertise in computer science, mathematics, 3D graphics, and machine learning, often backed by a degree in a related field. Experience with programming languages (such as Python, C++, and CUDA), 3D engines (like Unity or Unreal Engine), and AI frameworks (like TensorFlow or PyTorch) is typically required. Creativity, problem-solving skills, and effective communication are crucial soft skills for developing innovative solutions and collaborating with multidisciplinary teams. These skills and qualities are vital to successfully design, implement, and optimize intelligent 3D systems that meet technical and user requirements.

What are some typical challenges 3D AI engineers face when integrating AI algorithms with real-time 3D graphics?

3D AI Engineers often encounter the challenge of balancing computational efficiency with the complexity of AI models, especially when deploying them in real-time 3D environments such as games or simulations. Ensuring smooth performance while maintaining high-quality visuals and intelligent behaviors requires close collaboration with graphics programmers and optimization specialists. Additionally, staying updated with the latest advancements in both AI and 3D rendering technologies is essential for overcoming integration hurdles and delivering innovative solutions.

What is the difference between 3D Ai Engineer vs 3D Artist?

Aspect3D Ai Engineer3D Artist
Required SkillsAI algorithms, programming, 3D modelingCreative design, modeling, texturing
Work EnvironmentTech companies, AI labs, software developmentMedia, entertainment, gaming, advertising
CertificationsComputer Science, AI, 3D modeling softwareDesign, art, 3D software certifications

While both roles involve 3D work, 3D Ai Engineers focus on integrating AI with 3D technologies, requiring programming and AI expertise. 3D Artists primarily focus on creating visual content using artistic skills. The roles often overlap in industries like gaming and entertainment but differ in technical and creative emphasis.

Is AI taking over 3D Ai engineering jobs?

3D AI engineering is a specialized field that combines 3D modeling, AI algorithms, and machine learning skills. While automation and AI tools are transforming the industry, demand for skilled engineers remains strong due to the need for complex problem-solving, creativity, and expertise in AI integration within 3D environments.

Is a 3D Ai engineer still in demand?

A 3D AI engineer remains in demand due to the growing use of AI in 3D modeling, animation, and virtual environments. Skills in machine learning, computer vision, and proficiency with tools like Blender or Unreal Engine enhance job prospects in this evolving field.
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3D Ai Engineer jobs near you
Infographic showing various 3D Ai Engineer job openings in the United States as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $145,359 per year, or $69.9 per hour.

AI Engineer - Robotics Data Preprocessing

Pensacola, FL • On-site

Persona AI
See more jobs at Persona AIexternal

$108K - $130K/yr

Full-time

Medical, PTO

Posted 6 days ago

Job description

Job Title: AI Engineer - Robotics Data Preprocessing
Department: Software
Reports To: Teleoperations Lead
Employment Type: Full-Time
Location: Houston, TX or Pensacola FL
Who We Are
Persona AI is building humanoid robots for the most demanding environments in heavy industry - shipyards, steel mills, fabrication facilities, and offshore platforms - performing welding, grinding, maintenance, inspection, and material-handling work that is dangerous, physically demanding, and increasingly difficult to staff.
We are backed by leading strategic and financial investors and engaged with global industrial leaders across Korea, Japan, the United States, and Singapore. Korea is the center of gravity for our early commercial strategy, anchored by relationships with the world's leading shipbuilders and steelmakers. Our work spans both the robot platform itself and the systems, partners, and playbooks required to deploy it at scale.
Why Join Persona AI?
  • We offer competitive compensation, a performance-based bonus, 99% employer covered medical benefits, early-stage equity, competitive PTO, and a company-wide paid winter break between December 24th and January 2nd.
  • You'll shape technology that's redefining the possibilities of robotics and human interaction.
  • Work alongside passionate teammates who value creativity, and continuous learning.
  • Enjoy full access to advanced tools,

About the Role
At Persona we require an unprecedented volume of high-quality, multimodal data. We are moving beyond basic teleoperation to leverage massive datasets of in-the-wild egocentric video combined with dense sensor streams (IMU, haptics, kinematics, and high-fidelity force profiles). We are seeking a highly skilled AI Engineer to architect the systems that turn this raw, unstructured multimodal data into high-fidelity training assets for our robots.
Models are only as good as the data they learn from. In humanoid robotics, that's not a platitude, it's the bottleneck. There's no Internet-scale corpus of robots manipulating the physical world. We have to create it. That's this role.
As an AI Data Engineer, you sit at the most leveraged point in our entire training pipeline: every model we ship is downstream of the data you build. If this role succeeds, our foundation models learn dexterity faster than anyone else's. If it fails, nothing else matters.
You will architect and scale the infrastructure that turns raw, messy reality into training-grade data, extracting, augmenting, and aligning human dexterous manipulation data from massive multi-sensor and egocentric video datasets. You'll build advanced pre-processing algorithms that recover what sensors can't directly see: quantifying grasp dynamics from force-torque signals, estimating contact forces from visual cues alone, reconstructing heavily occluded hand poses, and lifting 3D geometry out of 2D frames.
And because every minute of teleoperation data is expensive, you'll make each one count: using spatial, temporal, and cross-modal augmentation to multiply the value of everything our collection team captures. Your work directly determines how fast our models learn and how far they can go.
What You Will Be Doing
  • Force Analysis & Hidden State Inference: Design cross-modal validation systems that verify video, proprioception, force/haptic signals, and language annotations agree with each other, e.g., reprojecting robot state into the image plane to confirm video-state consistency, and VLM-assisted checks that instructions match observed behavior.
  • Kinematic Retargeting & Alignment: orchestrating hand-tracking, segmentation, depth estimation, 3D reconstruction, and pose-tracking modules; retargeting human demonstrations into robot trajectories; and running simulation-in-the-loop validation (kinematic feasibility, physics replay, motion-consistency filtering) so synthesized data is physically grounded, not just visually plausible.
  • Advanced Data Augmentation: Implement robust data augmentation strategies (spatial transformations, temporal scaling, synthetic viewpoints, and sensor noise injection) to expand expert trajectories and improve the robustness of our learning models.
  • Teleoperation Synchronization: unified state-action representations across differing embodiments, coordinate frames, rotation conventions, gripper/hand parameterizations, and sampling rates, with per-dimension validity masking and per-source normalization so that adding a new robot or sensor is a configuration change, not a rewrite.
  • Close the loop with data consumers: build the tooling that lets researchers query, visualize, and audit datasets (clip browsers, trajectory viewers, annotation review UIs), and turn model-failure analyses into new curation rules and targeted re-collection requests.
  • Multimodal Data Pipelines: Architect end-to-end ingestion pipelines that take raw, unstructured recordings (egocentric video, teleoperation sessions, third-party open datasets) and produce indexed, queryable, training-ready datasets. This includes temporal segmentation of long recordings into action clips, metadata and scene-graph extraction, embedding-based retrieval, and language annotation workflows.

What We Are Looking For
  • Education: M.S., or Ph.D. in Computer Science, Data Engineering, Machine Learning, Robotics, or a related field.
  • Programming & ML Frameworks: Deep expertise in Python and extensive experience with PyTorch, specifically in handling custom dataloaders for multimodal datasets.
  • Force & Time-Series Data Processing: Experience analyzing and processing complex time-series data from force-torque (F/T) sensors, load cells, or tactile arrays, ensuring pristine alignment with visual frames.
  • Video Processing Expertise: Mastery of video processing pipelines and libraries (OpenCV, FFmpeg, Decord) and managing the I/O bottlenecks of terabyte-scale video datasets.
  • Solid working knowledge of 3D geometry and robotics data: coordinate frames and transforms, rotation representations, camera intrinsics/extrinsics, forward/inverse kinematics, URDF.
  • Data Augmentation: Proven ability to implement programmatic and generative data augmentation techniques for computer vision and time-series data.

Bonus Skills
  • Experience with NVIDIA's robotic software stack (Open X-Embodiment, DROID, AgiBot World, EgoDex, or similar).
  • Familiarity with the modern perception toolbox as a user: segmentation (SAM-family), monocular depth, hand/body pose estimation (MANO/SMPL), 6-DoF object pose tracking, point tracking-you don't need to train these models, but you should be comfortable composing and evaluating them in a pipeline
  • Familiarity with distributed data processing systems (Ray, Apache Spark) for cluster computing.
  • Background in generating or utilizing synthetic robotic data via simulation (Omniverse, MuJoCo).
  • Experience integrating spatial awareness or tactile data representations (e.g., Fourier encoding) into visual pipelines.

Persona AI is an Equal Opportunity Employer.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, age, disability, veteran status, or any other characteristic protected by applicable federal, state, or local law.

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