---
title: 'Staff Software Engineer, ML Infrastructure at Voxel'
canonical: 'https://feeny.ai/job/staff-software-engineer-ml-infrastructure-voxel-san-francisco-xwysrhxfmk6g'
type: 'job'
last_seen: '2026-09-11'
---

# Staff Software Engineer, ML Infrastructure at Voxel

- **Company:** Voxel
- **Location:** San Francisco, CA
- **Compensation:** $220k–$260k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-05-06
- **Last confirmed live:** 2026-09-11
- **Apply:** https://jobs.ashbyhq.com/voxel/6b1200b8-5bf8-4496-abc2-5bd124e2aeaf

## Job description

## Who We Are

Voxel is building the future of Computer Vision and Machine Learning for operations, risk, and safety. We use computer vision and AI to enable existing security cameras to automatically detect hazards and high-risk activities, keep people safe and drive operational efficiencies. Our technology addresses the key cost drivers for workers’ compensation, general liability, and property damage, which cost US employers over $500 billion annually. Our customers include Fortune 500 companies across grocery, retail, manufacturing, food and beverage, logistics, and pharmaceutical distribution. We’ve passed $10M ARR with strong expansion revenue. Based in SF, backed by industry-leading VCs.

## About the Role

Voxel’s perception system is the technical core of everything we ship. Our models detect human activity, equipment interactions, environmental hazards, and operational state in real time across thousands of cameras in manufacturing, logistics, retail, and pharmaceutical environments. Safety was our wedge; it proved our platform works. Now customers are pulling us into operations: equipment utilization, workflow compliance, process efficiency. Every new use case runs through the perception team. We're hiring a Staff Software Engineer to own ML Infrastructure at Voxel. Our applied ML team is shipping vision models into production every week, across thousands of cameras at Fortune 500 customers, and the infrastructure underneath determines how fast we can move. You'll set the technical direction for how we train, track, and ship vision models, build the foundational systems that the applied ML team relies on, and shape the architectural decisions that will define our ML stack for the next several years. This is a hands-on role. You'll write code, make architecture calls, and own outcomes end to end. You'll partner closely with applied CV engineers, the ML Data team, and the Platform team, and you'll be the technical voice in the room when ML infrastructure tradeoffs come up.

## What You'll Do

- Set the technical direction for ML infrastructure at Voxel: what we build, what we buy, and how the pieces fit together as the team and model portfolio scale
- Architect and build the training infrastructure that lets the applied ML team run multiple experiments concurrently and iterate quickly on new architectures (PyTorch, AWS)
- Own the train-to-deploy handoff: export trained models to optimized inference formats (TensorRT, ONNX), quantify accuracy and latency impact, and partner with Platform on production deployment
- Pick and roll out the experiment tracking and lifecycle stack (Weights & Biases, MLflow, ClearML, or similar) so researchers can run, compare, and reproduce experiments efficiently
- Establish DevOps-for-ML best practices (IaC, CI/CD, observability, cost monitoring) so researchers can iterate quickly and safely
- Mentor engineers across Vision & AI on ML infrastructure best practices, raising the bar for how the org thinks about training, evaluation, and deployment
- Anticipate where the infrastructure needs to be in 12 to 18 months, including the upcoming move to on-device inference, and architect for that future

## What We're Looking For

- 7+ years building and shipping large-scale software systems, with at least 3 years focused on ML infrastructure or large-scale data infrastructure
- A track record of being the person who decides the architecture, not just the person who implements it. You've owned tool selection, framework choices, and build-vs-buy calls for systems other engineers depend on
- Deep fluency in PyTorch and the modern ML training stack. You know what good experiment tracking looks like, what makes a training pipeline reliable at scale, and where the failure modes live
- Strong Python. Performant, maintainable code that holds up in production
- A pragmatic shipping orientation. You can tell the difference between architectural decisions that need to be right and ones that can be revisited later, and you don't over-engineer the latter
- Strong communication skills. You can explain complex tradeoffs clearly to ML researchers, infra peers, and leadership

## Nice to Have

- Production experience on AWS (S3, EC2, EKS, or similar) for ML workloads
- Hands-on experience with model export and inference optimization (TensorRT, ONNX, or similar), including measuring accuracy and latency tradeoffs against training-time baselines
- Experience with modern ML orchestration tools (Ray, Sematic, Flyte, Metaflow, Prefect, or similar)
- Familiarity with GPU performance profiling and optimization (Nsight, PyTorch profiler, or similar)
- Background in computer vision model training

## Compensation & Benefits

- Equity through Voxel’s Equity Incentive Plan
- Total compensation includes base salary, annual bonus, and equity
- Comprehensive health, dental, and vision insurance
- Competitive paid parental leave
- Unlimited PTO and flexible work arrangements
- Daily meals in-office, team events, annual company onsite

## About Voxel

## Company Overview
- **One-liner**: Voxel provides an AI-powered site intelligence platform that uses existing camera infrastructure to proactively identify and reduce workplace safety and operational risks in industrial environments.
- **Entity Type**: Private (Series B, $44M–$47M raised in mid-2025)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2020
- **Founders**: Troy Carlson (Co-Founder) — other co-founders not publicly disclosed

## Core Business
- **Primary Industry**: Workplace safety technology, AI computer vision, industrial operations risk management
- **Target Customers**: B2B, Fortune 500 companies across manufacturing, warehousing, food & beverage, supply chain, logistics, and retail
- **Mission**: “Redefine safety and operations in the workplace using AI for the betterment of all.” [voxelai.com/about](https://www.voxelai.com/about)

## Products & Services
- **Voxel Site Intelligence Platform (end-to-end)**: A SaaS platform that ingests video from existing IP cameras, applies AI computer vision to detect safety risks (ergonomics, PPE, vehicles, environmental hazards), surfaces actionable insights, and enables workflow management (task assignments, coaching, reporting). [voxelai.com](https://www.voxelai.com/)
- **Executive Hub**: Executive-level dashboard providing enterprise-wide visibility into safety performance, risk trends, and team accountability. [voxelai.com/news](https://www.voxelai.com/news)
- **Risk Insights**: AI-powered daily safety snapshots delivered to stakeholders to drive immediate action. [voxelai.com/news](https://www.voxelai.com/news)
- **Actions Feature**: Converts detected risks into recommended actions with owner assignment, deadlines, and impact tracking. [voxelai.com/news](https://www.voxelai.com/news)

## Market Standing
- **Valuation**: Not publicly disclosed
- **Key Metric – Total Funding**: $77.0M raised to date across multiple rounds [linkedin.com](https://www.linkedin.com/company/voxelai):
  - Seed Round (Oct 2021): $3.0M led by MTech Capital
  - Series A (May 2022): $15.0M led by Eclipse
  - Venture Round (Aug 2023): $12.0M led by Rite-Hite
  - Series B (Jun–Jul 2025): conflicting reports of $44M [voxelai.com/news](https://www.voxelai.com/news) and $47M [linkedin.com](https://www.linkedin.com/company/voxelai); led by NewRoad Capital Partners
- **Key Metric – Annual Revenue**: Estimated $6.3M (LinkedIn data) [linkedin.com](https://www.linkedin.com/company/voxelai)
- **Notable Investors**: Eclipse, NewRoad Capital Partners, Rite-Hite, Ericsson Ventures, MTech Capital [voxelai.com/news](https://www.voxelai.com/news)
- **Notable Partners/Advisors**: Chris Sultemeier (former Walmart EVP, joined board); Novara (mutual referral partnership) [voxelai.com/news](https://www.voxelai.com/news)
- **Growth Signals**:
  - 147% year-over-year growth in 2025 [voxelai.com/news](https://www.voxelai.com/news)
  - Deployed across 250+ sites worldwide [voxelai.com/about](https://www.voxelai.com/about)
  - 65% average reduction in workers’ compensation claims [voxelai.com/about](https://www.voxelai.com/about)
  - International expansion to five continents (10+ countries) [voxelai.com/news](https://www.voxelai.com/news)
  - Team size grew 44% YoY to ~96 employees [linkedin.com](https://www.linkedin.com/company/voxelai)

## Competitive Advantages
- **Purpose-built AI**: Models trained on 5+ billion hours of real-world industrial workplace scenarios, achieving 95%+ detection accuracy [voxelai.com](https://www.voxelai.com/)
- **Rapid deployment**: Works with 95% of existing IP cameras; deploys to any site in 48 hours [voxelai.com](https://www.voxelai.com/)
- **Privacy-first design**: No facial recognition, face/body blurring, SOC 2 Type II certified, ISO 27001-certified data centers, end-to-end encryption [voxelai.com](https://www.voxelai.com/solutions-safety)
- **Platform stickiness**: End-to-end from detection to resolution, including workflow engine and executive reporting, creating a comprehensive safety intelligence layer.

## Strategic Focus
- **International expansion**: Scaling presence across Europe, Asia, and other regions with local deployments and partnerships [voxelai.com/news](https://www.voxelai.com/news)
- **Product innovation**: Continuously adding features (Risk Insights, Actions, Executive Hub) to deepen the platform’s value
- **Enterprise go-to-market**: Targeting Fortune 500 and large multi-site industrial customers
- **Hiring growth**: Expanding engineering, sales, and customer-facing teams; grew San Francisco HQ in 2026 [voxelai.com/news](https://www.voxelai.com/news)

## Why Work Here
- **Mission-driven culture**: Focus on protecting essential industrial workers from preventable injuries — a strong purpose that motivates the team [voxelai.com/about](https://www.voxelai.com/about)
- **Growth trajectory**: Rapidly scaling company (44% headcount growth, 147% revenue growth) offering career advancement opportunities
- **Technical environment**: Full-stack AI and computer vision engineering working on real-time, high-impact safety challenges
- **Global & remote-friendly**: Team members across the US, Canada, Bulgaria, Netherlands, and Pakistan; hybrid/remote policy not explicitly stated but geographically distributed [linkedin.com](https://www.linkedin.com/company/voxelai)
- **Employee ratings**: 4.0/5.0 on LinkedIn (based on 4 reviews), with highlights in Career (3.6) and Culture (3.3) [linkedin.com](https://www.linkedin.com/company/voxelai)
- **Open roles** (as of mid-2026): Tech Lead Manager – Vision & AI, Senior Software Engineer – ML Data, Founding Forward Deployed Engineer, Senior Software Engineer – ML Infrastructure, Staff Software Engineer – ML Infrastructure, Product Designer [linkedin.com](https://www.linkedin.com/company/voxelai)

## Sources
1. [voxelai.com – Homepage](https://www.voxelai.com/)
2. [voxelai.com – About page](https://www.voxelai.com/about)
3. [voxelai.com – Solutions Safety page](https://www.voxelai.com/solutions-safety)
4. [voxelai.com – Newsroom](https://www.voxelai.com/news)
5. [linkedin.com – Voxel company page](https://www.linkedin.com/company/voxelai)

## Other roles at Voxel

- [Tier 2 Support Engineer](https://feeny.ai/job/tier-2-support-engineer-voxel-remote-2f4perx8tk6j)
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- [Software Engineer, Perception](https://feeny.ai/job/software-engineer-perception-voxel-san-francisco-fmtpwpwcf717) — San Francisco, CA
- [Tier 3 Support Engineer](https://feeny.ai/job/tier-3-support-engineer-voxel-remote-meknxb53c2kz)
- [Enterprise Account Executive, Industrial & Supply Chain](https://feeny.ai/job/enterprise-account-executive-industrial-supply-chain-voxel-remote-5qef57ygsrn2)
- [Senior Software Engineer, ML Infrastructure](https://feeny.ai/job/senior-software-engineer-ml-infrastructure-voxel-san-francisco-97feys5szawr) — San Francisco, CA
- [General Opportunity](https://feeny.ai/job/general-opportunity-voxel-remote-vpzwy9v9ghg4)
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