SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Mach9 Robotics is building AI-enabled CAD systems powered by perception models that extract 3D object and line features from LiDAR point clouds and imagery. As an ML Engineer on the Product team, you will work directly with customers to develop computer vision and ML pipelines that solve real-world problems for surveyors and engineers in the field.
You will own features end-to-end: from scoping with product and customer-facing teams, through data and labeling strategy, model selection or fine-tuning, evaluation, and integration into the Digital Surveyor product. This is a hands-on role where you ship frequently and iterate based on customer feedback and performance metrics.
Your responsibilities include:
- Ship new extraction features end-to-end, managing the full lifecycle from requirements through production integration
- Build on existing model families and open-source tooling (vision foundation models, VLMs, point-cloud backbones, classical geometry)
- Adapt production models to new object classes, regions, and sensor types as customer needs evolve
- Build evaluation pipelines that measure improvements and catch regressions
- Iterate on feature extraction pipelines based on customer feedback and metric changes
This role is ideal for early-career engineers (new grad to ~3 years) who learn fast, are curious about how things work, and get real satisfaction from shipping working code. You will need to come up with ideas, try them, get feedback, and iterate quickly.
REQUIREMENTS:
- BS or MS in Computer Science, EE, Robotics, or related field, or equivalent experience
- Strong coding abilities, preferably Python and PyTorch, comfortable working with large codebases
- Hands-on experience training or fine-tuning a vision model (segmentation, detection, or 3D) through work, internships, or projects
- Working knowledge of 3D perception geometry: coordinate systems, transforms, projecting between images and point clouds
- Curiosity and speed: pick up new frameworks and papers quickly, explain learnings to teammates
- Clear communicator with engineers, product teams, and end-user surveyors
- Fluent with AI coding assistants
BONUS QUALIFICATIONS:
- Experience with open-source vision foundation models (SAM family, DINO, Grounding DINO, or similar)
- Experience with point clouds or LiDAR data (Open3D, PDAL, PyTorch3D, sparse convolution libraries)
- Experience deploying models to production (ONNX, TensorRT, batch inference on cloud GPUs)
