data
Posted 1 weeks agoML Engineer
at Mach9
San Francisco, United StatesOn-site
Responsibilities
- - Own models through the full product lifecycle: problem framing, data strategy, training, evaluation, and final integration into our cloud-based CAD software, Digital Surveyor.
- - Develop evaluation methodology and metrics that reflect real surveying and engineering accuracy requirements.
Requirements
- THE ROLE At Mach9, ML Engineers build the perception models at the core of our AI-enabled CAD system.
- Our unique data advantage allows us to develop and train cutting edge 3D scene understanding models that serve real surveyors and engineers in the field.
- This role is ideal for early-to-mid-career ML engineers who thrive on end-to-end ownership and are able to move fluidly from dissecting a new architecture paper to shipping the product feature that the resulting ML model backs.
- 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: prototyping new approaches, running experiments, and identifying what’s shippable.
- - Work with ML infrastructure engineers to scale training and inference of your models and with product teams to align your model’s behavior with what the user wants.
- experience training models for segmentation, detection, or 3D understanding. -
- Experience taking a ML model from research/prototype to production, not just publishing or benchmarking. - Working knowledge of geometric concepts relevant to 3D perception like coordinate systems and 3D transforms. - Strong communication skills and the ability to collaborate with researchers, other engineers and product stakeholders. - Proficient with Python and a production-quality ML library like PyTorch, JAX, or TensorFlow. BONUS QUALIFICATIONS -
- Experience with common 3D deep learning architectures, like point cloud backbones such as PTv3, sparse convolutions, or 3D detection/segmentation networks. -
- Experience with large unstructured datasets — imagery and 3D point clouds — at scale. -
- Experience delivering production-grade models with optimization techniques such as quantization, pruning, distillation, or runtime acceleration (e.g., TensorRT, ONNX Runtime). - Familiarity with multi-GPU training and experiment management (Weights & Biases or similar). - Publications or strong open-source contributions in computer vision or 3D machine learning.
Benefits
- 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
Additional details
- We build models to extract 3D object and line features from dense LiDAR point clouds and imagery.
- This role is both research-driven and product-focused.
- You'll design and train the models that power our automated extraction pipeline — image and 3D detection and localization — and work end-to-end from research prototype to production feature.
- You'll partner closely with infrastructure and product teams to take ideas from a paper to deployed capabilities.