Search
Go
This job is no longer accepting applications
This listing was closed on Jul 17, 2026.
Browse Open JobsML Engineer
Summary by AIEngineer.careers
ML Engineer is a AI Engineer role (full-time). with Mach9 Robotics Inc. in SAN FRANCISCO, US. Imported listing (source: ziprecruiter.com). Apply on the employer's site (ziprecruiter.com).
Imported listing (source: ziprecruiter.com) · Apply on ziprecruiter.com
SAN FRANCISCO · US
—
Full-time
MID
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from ziprecruiter.com
Mach9 Robotics is seeking an ML Engineer to build perception models for AI-enabled CAD systems, focusing on 3D object and line feature extraction from LiDAR point clouds and imagery. The role involves end-to-end ownership from research to production.
Responsibilities
- Design, train, and evaluate computer vision and 3D ML models for extracting CAD-grade geometry from LiDAR and imagery.
- Drive ML research translating into product capabilities, prototyping, and identifying shippable features.
- Own models through full product lifecycle: problem framing, data strategy, training, evaluation, and integration.
- Develop evaluation methodology and metrics reflecting real surveying accuracy requirements.
- Collaborate with ML infrastructure and product teams to scale training and align model behavior.
Requirements
- Master's or PhD in ML, Computer Vision, CS, or related field, or equivalent experience.
- Strong foundation in computer vision and deep learning with hands-on experience in segmentation, detection, or 3D understanding.
- Experience taking ML models from research to production.
- Working knowledge of geometric concepts for 3D perception.
Mach9 Robotics Inc
San Francisco · US · 27+ employees
Mach9 builds software that transforms reality capture datasets (like LiDAR) into high-precision 3D maps and engineering deliverables. Its flagship product, Digital Surveyor, automates feature extraction for infrastructure and engineering teams.
