Staff Software Engineer, Voxel
ML Infrastructure
$200-250k
+ Equity Incentive Plan
Computer vision for security cameras
Open for applications
Computer vision for security cameras
21-100 employees
Open for applications
$200-250k
+ Equity Incentive Plan
21-100 employees
Company mission
To pioneer new standards for enterprise EHS and operations teams through innovative technology.
Role
Who you are
- If you excel at designing cloud-native, distributed systems that turn raw video into production-ready, version-controlled models, we’d love to meet you
- Bachelor’s (or higher) in Computer Science, EE, or related field
- 5+ years building and operating large-scale infrastructure, with at least 3 years focused on ML or data-intensive systems
- Proven record designing highly available, distributed systems on Kubernetes (EKS, GKE, or on-prem)
- Deep expertise with orchestration (K8s operators, Argo, Kubeflow), and cluster-scale storage / compute (S3, GCS, Ray, Spark, Dask)
- Hands-on experience automating data-labeling or ground-truth workflows and maintaining dataset versioning
- Strong software-engineering fundamentals; familiar with best practices for testing, observability, and secure coding
- Demonstrated DevOps mindset — IaC (Terraform/CDK), CI/CD (GitHub Actions, ArgoCD), metrics & alerting (Prometheus/Grafana)
Desirable
- Experience running multi-instance / multi-GPU training jobs, mixed-precision optimizations, or TensorRT / Triton inference
- Familiarity with active-learning, continuous-training, or online distillation pipelines
- Background in model registry tooling (MLflow, BentoML, SageMaker Registry) and evaluation dashboards
- Prior work with computer-vision models (YOLO, DETR, Faster RCNN) or video understanding at scale
- Contributions to open-source ML infra projects or published talks/blogs on MLOps
- Exposure to edge-deployment or real-time inference systems
- Experience shipping high quality production code in Python
What the job involves
- Voxel is looking for a Staff Machine-Learning Infrastructure Engineer to drive the next wave of our computer-vision platform for workplace safety
- You will be the technical owner for three pillars of our ML lifecycle — ground-truth data & labeling workflows, large-scale training infrastructure, and continuous model lifecycle management
- Own data & labeling pipelines – architect scalable labeling services (storage, query, retrieval), design ontologies, automate annotation workflows, and build quality-tiered datasets that stay within cost constraints
- Build and operate training infrastructure – create multi-GPU / multi-node training frameworks (Ray, Spark, Kubernetes), optimize distributed jobs, and integrate accelerators (TensorRT, CUDA-graph, FP8, etc.)
- Manage the full model lifecycle – stand up model registries, version control, evaluation suites, and continuous-learning loops that push updates from dev → staging → prod with zero-downtime rollbacks
- Provide technical leadership, mentorship, and lightweight project management to a small infra + research squad
- Establish DevOps-for-ML best practices (IaC, CI/CD, observability, cost monitoring) so researchers can iterate quickly and safely
- Partner with ML engineers on architecture decisions, from data schemas to inference optimizations, ensuring infra and research road-maps stay tightly aligned
Our take
Industry warehouses are vital to the world's economy, but workplace injuries remain a real and present danger to workers. Voxel solves this problem with its AI-powered security cameras, designed to monitor environments and detect hazards.
Voxel's AI integrates with existing security cameras to detect safety risks, from spills to near-miss vehicle collisions. Once a hazard is identified, it alerts key personnel, enabling immediate action. This proactive system has significantly reduced workplace injuries, with like like Michale's, Dollar Tree, and Clorox seeing accident rates drop by up to 80%, while also improving operational efficiency.
Since its launch in 2020, it has raised $30M. With this substantial funding under its belt, Voxel is working to expand its reach to new industries like ports and airports. With this commitment to demonstrating AI's positive impact, the space is an exciting one for Voxel.
Steph
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 4 rounds)
Jun 2025
$44m
SERIES B
Aug 2023
$12m
EARLY VC
Total funding: $74m
Company benefits
- Extensive / Generous health, dental, and vision insurance
- Highly competitive paid parental leave and support system
- Ownership in the business through an Equity Incentive Plan
- Generous paid time off and / or flexible work arrangements
- Daily meals in-office, vibrant company events, team-building
- 401K retirement plan, HSA options, pre-tax Commuter Card
Company HQ
SoMa, San Francisco, CA
Leadership
Anurag Kanungo
(Co-Founder & CTO)Worked as a Software Engineer at the Foundation for Learning Equality and Intuit. Co-founded Medopad before joining Uber as a Senior Autonomy Engineer.
Harishma Dayanidhi
(Co-Founder)Previously worked as a Software Engineer at Uber and Aurora.
Troy Carlson
(Co-Founder)Previously worked as a Software Engineer at companies including OWL Computing and Google.
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