Director of Machine Learning & 3D Reconstruction
US$200,000 – US$270,000 / yr base salary
Posted 22 Apr 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 7+ yrs
- Management level
- People management
- Employment
- Hybrid
- Contract
- Full-time
- Visa sponsorship
- Not offered
| Base salary | US$200,000 – US$270,000 / yr |
|---|
Field of studyComputer Science, Electrical Engineering (or related)
Study levelBachelor's or higher
Study levelDoctorate
Quidient is a deep tech AI company pioneering advancements in Generalized (5D) Scene Reconstruction (GSR). GSR is poised to become one of the world’s great digital product categories (think GPS, MRI, and LMM). Our flagship GSR product, Quidient Reality®, is a powerful API that enables anyone with a mobile device to virtualize, visualize, and measure anything. Words relevant to Quidient include Generative AI, Physics-Informed AI, Large Scene Models (LSMs), Large World Models (LWMs), and API-First.
Overview
Quidient is seeking a Director of ML & Reconstruction to lead applied machine learning improvements across our Generalized Scene Reconstruction Platform. You will own the ML engineering function within our Product Development group, driving quality improvements in our 3D scene reconstruction pipeline, while building and managing a high-performing team of engineers and applied scientists.
This is a leadership-first role. You will manage cross-functional workstreams across the Applications & API, Platform, and Advanced Product Development teams. You will translate technical tradeoffs into delivery decisions and contribute meaningfully to the codebase where your domain expertise drives the most value. You will ship production ML into a system already in customers’ hands. This position is full-time, hybrid, and reports to Quidient’s Director of Software Engineering.
What You’ll Do
ML & Reconstruction Quality
- Drive ML-driven quality improvements across the production 3D scene reconstruction pipeline, including panel geometry, background reconstruction, and output fidelity.
- Own model selection, deployment, inference optimization, and operational ownership of ML systems in production.
- Evaluate and apply traditional ML and applied deep learning techniques to improve reconstruction quality; understand when each approach is appropriate.
- Review and contribute to the production codebase, evaluate tradeoffs, identify bottlenecks, and guide technical decisions.
Team Leadership & Cross-Functional Coordination
- Build, manage, and grow a team of ML engineers and applied scientists within the Advanced Product Development team.
- Drive cross-functional alignment across the Applications & API and Platform teams.
- Partner with the APD technical leads and Director of Software Engineering to scope work, resolve technical blockers, and maintain delivery velocity.
- Operate effectively in a fast-moving startup where priorities shift; maintain focus on the highest-impact work without losing team momentum.