---
title: 'ML Engineer at Mach9'
canonical: 'https://feeny.ai/job/ml-engineer-mach9-san-francisco-x1bf09p00g77'
type: 'job'
last_seen: '2026-09-06'
---

# ML Engineer at Mach9

- **Company:** Mach9
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Posted:** 2026-06-03
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/mach9/51061973-9726-4e8e-bba4-4bfa9e3ef004

## Job description

## THE ROLE

At Mach9, ML Engineers build the perception models at the core of our AI-enabled CAD system. We build models to extract 3D object and line features from dense LiDAR point clouds and imagery. 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 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.

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.
- 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.
- 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.

## 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 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.

## About Mach9

## Company Overview
- **One-liner**: Mach9 builds AI-native CAD software that automatically transforms LiDAR point clouds into engineering-grade 3D maps, accelerating infrastructure design and surveying workflows.
- **Entity Type**: Private (Seed stage)
- **Headquarters**: San Francisco, California, USA
- **Founded**: 2021
- **Founders**: Alexander Baikovitz (CEO), Zachary Sussman (CTO), Haowen Shi, Michael M. – four researchers from Carnegie Mellon University's Robotics Institute.

## Core Business
- **Primary industries**: Civil infrastructure, surveying & geospatial services, transportation, telecom, utilities, architecture/engineering/construction (AEC).
- **Target customers**: B2B. Enterprise clients include top engineering firms (Langan, Olsson, Woolpert, HDR, Michael Baker International), major state Departments of Transportation (DOTs), and utility companies.
- **Mission/purpose**: "Accelerate how teams model and understand the world" – providing the fastest, most accurate automated feature-extraction technology for infrastructure projects.

## Products & Services
- **Digital Surveyor (DS2)**: AI-native, web-based CAD platform for automated feature extraction from LiDAR point clouds. Offers AI-assisted extraction (curbs, pavement edges, guardrails, utility poles), manual tools, and direct export to AutoCAD, MicroStation, and ESRI. Data-agnostic ingest pipeline supports scanners from RIEGL, Trimble, Leica, NavVis. Type: SaaS.

## Market Standing
- **Valuation**: Not publicly disclosed.
- **Key Metric**: Total Funding – **USD $14,425,000** (as of early 2026).
- **Notable Investors/Partners**: Y Combinator (Summer 2021 batch), Quiet Capital (led $12M Seed round, Nov 2024), Tiger Global Management (led $2.3M Seed round, Dec 2021), and top executives from Cruise, Autodesk, Adobe, and DoorDash as advisors/investors.
- **Growth Signals**: Headcount of 30 employees (LinkedIn, Apr 2026) with +32.1% yearly growth; monthly job posting growth +66.7% year-over-year; trusted by leading engineering firms and state DOTs; launched Digital Surveyor 2 in March 2026; featured in Geo Week News and YC blog.

## Competitive Advantages
- **AI-native CAD workflow**: Unlike traditional manual drafting, DS2's AI "drafts with you" – learning from user edits to improve suggestions in real time, cutting manual drafting time by up to 96×.
- **Field-to-finish in one environment**: No need to switch between preprocessing, extraction, and CAD tools – all done in a single web-based platform.
- **Strong research roots**: Built on decades of research from Carnegie Mellon University's Robotics Institute, giving a deep technical moat in computer vision and geospatial ML.
- **Designed for surveyors**: Intuitive UI that lets domain experts (not just CAD specialists) be productive on day one.

## Strategic Focus
- **Scale GTM and engineering**: Active hiring across sales (Account Executive, Founding Marketer), engineering (ML Infrastructure Engineer, Perception Software Engineer, Head of Product Engineering), and operations (Solutions Consultant, QA Survey Technician).
- **Expand into new verticals**: Targeting electric/telecom utilities, data centers, and broader infrastructure beyond transportation.
- **Product evolution**: Continuously improving AI accuracy and automation, with a focus on trust and user control (as highlighted in the DS2 launch).

## Why Work Here
- **Culture**: Fast-paced, customer-obsessed, engineering-first environment. Values: "work fast, iterate with customer feedback, never compromise on excellence."
- **Remote/Hybrid Policy**: HQ in San Francisco; some roles are "Remote / Remote (US)" per YC job listings. Likely hybrid with in-office presence for SF-based roles.
- **Perks & Benefits**: Health, vision, dental insurance; paid parental leave; flexible time off; equity package for all full-time employees; company 401(k); relocation assistance; catered lunches & paid dinner; company & team events; dog-friendly office.
- **Engineering culture**: Deep technical challenges at the intersection of AI, geospatial, computer graphics, and infrastructure. Opportunity to work on hard problems that "unlock billions in value for customers."

## Sources
1. [mach9.ai/careers](https://mach9.ai/careers)
2. [mach9.ai](https://www.mach9.ai/)
3. [mach9.ai/about](https://www.mach9.ai/about)
4. [ycombinator.com/companies/mach9](https://www.ycombinator.com/companies/mach9)
5. [linkedin.com/company/mach9geo](https://www.linkedin.com/company/mach9geo)

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