ML Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Salary

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401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Company stage

Seed From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

ML Engineer San Francisco 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

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