ML Engineer, Research
$180k - $300k • San Francisco • FullTime
Posted 4mo ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
On-site
Employment Type
FullTime
Categories
Machine Learning Engineer
About the job
At Mach9, ML Engineers build the perception models at the core of our AI-enabled CAD system, extracting 3D object and line features from dense LiDAR point clouds and imagery. This role is research-driven and product-focused, involving the design and training of models for image and 3D detection and localization. You will work end-to-end from research prototype to production feature, partnering closely with infrastructure and product teams to deploy capabilities. This position is ideal for early-to-mid-career ML engineers who excel at end-to-end ownership and can transition smoothly from dissecting research papers to shipping product features.
Responsibilities
- Design, train, and evaluate computer vision and 3D ML models for extracting CAD-grade geometry and features from dense LiDAR and imagery.
- Drive ML research that translates directly into product capabilities, including prototyping new approaches, running experiments, and identifying shippable features.
- Own models throughout the full product lifecycle: problem framing, data strategy, training, evaluation, and integration into cloud-based CAD software.
- Develop evaluation methodology and metrics that reflect real surveying and engineering accuracy requirements.
- Collaborate with ML infrastructure engineers to scale training and inference, and with product teams to align model behavior with user needs.
Requirements
- Master's or PhD in Machine Learning, Computer Vision, Computer Science, or a related field, or equivalent industry experience.
- Strong foundation in computer vision and deep learning, with hands-on experience training models for segmentation, detection, or 3D understanding.
- Experience taking an ML model from research/prototype to production.
- Working knowledge of geometric concepts relevant to 3D perception, such as coordinate systems and 3D transforms.
- Strong communication skills and ability to collaborate with researchers, engineers, and product stakeholders.
- Proficiency with Python and a production-quality ML library like PyTorch, JAX, or TensorFlow.