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Senior Machine Learning Engineer - 3D Reconstruction

Join Applied Intuition as a Senior Machine Learning Engineer to advance 3D reconstruction technology for autonomous vehicles.

Location
Sunnyvale, California, United States
Compensation
Not disclosed
Level
senior
Type
full time · On-site

Posted by employer 15 hours ago

First seen on Joblaze 2 hours ago

Last verified on the company career page 2 hours ago

Apply at Applied Intuition → Save job Scanned from appliedintuition.com

What you'll build

  • Advance learning-based reconstruction methods
  • Push limits of neural reconstruction for driving scenes
  • Explore feed-forward reconstruction approaches
  • Define evaluation metrics and validation workflows
  • Collaborate with customers to implement solutions

Must have

  • 5+ years of experience developing ML or computer vision systems
  • Bachelor's degree in computer science, physics, robotics, or equivalent
  • Strong hands-on experience with modern learning-based 3D reconstruction techniques
  • Solid foundation in multi-view geometry and camera models
  • Proficiency in Python and PyTorch

Nice to have

  • Experience with feed-forward or generalizable Gaussian Splatting
  • Background in computer vision or computer graphics
  • Track record of shipping ML products with evaluation metrics
  • Experience in autonomous driving or robotics
  • Peer-reviewed research at major conferences

Practical constraints

  • In-office work 5 days a week

Requirements

Experience
5+ years
Education
Bachelor's degree

Not disclosed in this posting: compensation, visa sponsorship.

Joblaze summary

In this role, the Senior Machine Learning Engineer focuses on enhancing the 3D reconstruction technology that underpins Applied Intuition's Neural Simulation product, working to improve the quality and scalability of simulations derived from real-world driving data. Key skills include expertise in modern 3D reconstruction techniques, proficiency in Python and PyTorch, and a solid understanding of multi-view geometry. This position is well-suited for experienced engineers with a background in machine learning or computer vision, particularly those who have a track record of deploying research into production. The team collaborates closely with various departments to deliver comprehensive solu

Joblaze insights

  • Listed today — first seen on Joblaze October 7, 2026. Last confirmed on Applied Intuition's careers page October 7, 2026.
  • Python appears in 53.1% of 544 comparable senior ai/ml roles in United States; CUDA appears in 4% of 544 comparable senior ai/ml roles in United States.

Quick facts

Is the Senior Machine Learning Engineer - 3D Reconstruction role remote?
No — this is an on-site role in Sunnyvale, California, United States.
How much experience is required?
At least 5 years of relevant experience for this Senior Machine Learning Engineer - 3D Reconstruction role.
Where is the role based?
Applied Intuition is hiring for this position in Sunnyvale, California, United States.
What's the tech stack?
Joblaze extracted these technologies from the posting: 3D Gaussian Splatting, C++, CUDA, NeRFs, PyTorch, Python.
What seniority level is this role?
Applied Intuition targets senior candidates for this position.
Is this full-time or contract?
Full-time for this Senior Machine Learning Engineer - 3D Reconstruction role at Applied Intuition.

From the original posting

About the role and team

We are looking for senior machine learning engineers to advance the core reconstruction technology behind Neural Simulation, our state-of-the-art product for turning real-world driving data into high-fidelity, photorealistic simulation environments. As part of this team, you will push the boundaries of what the product can do, raising reconstruction quality, scaling to ever-larger volumes of data, and making it more useful for customers who rely on it to train and validate their autonomy systems. Your work will directly shape how the largest OEMs in the world develop the next generation of data-driven autonomous vehicles.

This role is ideal for engineers who thrive at the intersection of 3D computer vision, graphics, and machine learning, and who are excited to take a state-of-the-art product further by bringing the latest research into production and solving the hardest simulation gaps in Physical AI.

At Applied Intuition, you will:

  • Advance the learning-based reconstruction methods at the core of our product, such as 3D Gaussian Splatting and NeRFs, bringing the latest research into production to improve fidelity, robustness, and scalability

  • Push the limits of neural reconstruction for large-scale, dynamic driving scenes, including:

    • Dynamic actor reconstruction and scene editing

    • Novel view synthesis and multi-sensor rendering (camera, LiDAR)

    • Scaling reconstruction quality and throughput across large volumes of fleet data

  • Explore and productionize feed-forward reconstruction approaches that reduce per-scene optimization cost and enable reconstruction at scale

  • Define and build evaluation metrics, benchmarks, and validation workflows that measure reconstruction fidelity and sim-to-real gap

  • Work closely with customers to understand their pain points and implement technical solutions in the Neural Simulation product

  • Collaborate closely with Infra, Autonomy, Research and other product teams to deliver end-to-end solutions

  • Take ownership of critical technical components and influence architecture and product decisions

We're looking for someone who has:

  • 5+ years of experience developing and shipping ML or computer vision systems

  • A minimum of a Bachelor's degree in computer science, physics, robotics, or equivalent

  • Strong hands-on experience with modern learning-based 3D reconstruction techniques, such as 3D Gaussian Splatting and NeRFs

  • A solid foundation in multi-view geometry, camera models, and differentiable rendering

  • Proficiency in Python and PyTorch, along with C++ and/or CUDA

  • A proven ability to turn research ideas into robust, production-quality software

  • Strong problem-solving skills and comfort with ambiguity

Nice to have:

  • Experience with feed-forward or generalizable Gaussian Splatting and reconstruction models

  • A background in computer vision (e.g., SfM, SLAM, photogrammetry) and/or computer graphics (e.g., rendering, rasterization, ray tracing)

  • A track record of shipping ML products with clearly defined evaluation metrics and benchmarks

  • Experience in autonomous driving or robotics, including working with multi-sensor data (camera, LiDAR, radar)

  • Peer-reviewed research at conferences such as CVPR, ICCV/ECCV, NeurIPS, SIGGRAPH, ICRA, or IROS

  • A Master's degree or PhD in computer science, physics, robotics, or related fields

Standard company text repeated across Applied Intuition's postings is omitted here.

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