Senior Software Engineer, ML Systems

Voxel

. Turn research ideas, including transformers, ensemble models, and new detection and classification approaches, into production features from prototype through evaluation, rollout, and iteration .

Posted 9/22/2026full-timeSan Francisco • California • United StatesSenior💰 $200,000 - $240,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and optimizing production machine learning and computer vision systems, with a strong focus on model serving, evaluation, and deployment. Proficient in Python and experienced with tools like Triton and TensorRT for inference optimization.

Highest-signal resume keywords

Production Machine Learning SystemsModel Serving and Inference OptimizationPython ProgrammingStreaming Data ProcessingTechnical Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningComputer VisionModel EvaluationInference OptimizationData ProcessingPythonC++GoTritonTensorRT

Soft Skills

MentoringTechnical Leadership

Tools & Technologies

FlinkKafkaKubernetesDockerTerraformArgoCDAWS

Industry Keywords

Production FeaturesDetection and ClassificationObservabilityCustomer DeploymentsData Lifecycle

Tech Stack

Tools & technologies

AWSDockerKafkaKubernetesPythonTerraformC++Go

About the role

Key responsibilities & impact

Turn research ideas, including transformers, ensemble models, and new detection and classification approaches, into production features from prototype through evaluation, rollout, and iteration
Design and build perception pipeline components on a stream-processing architecture using Flink/PyFlink
Work with the platform team on model serving, configuration management, and orchestration
Own and improve production computer vision models, including training, evaluation, and inference optimization using Triton, TensorRT, and multi-backend serving
Design logic that converts model outputs into trustworthy incidents through tracking, filtering, probabilistic reasoning, and state machines
Build observability through metrics, dashboards, and evaluation loops
Reduce end-to-end latency and cost while maintaining detection quality
Partner with GTM, customer success, and data operations on customer rollouts, deployment tuning, labeling, and review quality
Evaluate and integrate third-party ML tooling for orchestration, labeling, and dataset curation
Drive adoption of ML tooling across the team
Write design documents and requirements
De-risk major changes with proofs of concept
Provide technical leadership through design and execution without people management
Mentor teammates through design reviews, code reviews, and context sharing

Requirements

What you’ll need

5+ years building and shipping production ML or computer vision systems
Track record of moving techniques from research to reliable product
Strong Python
Working knowledge of C++ or Go is a plus
Experience with model serving and inference optimization, such as Triton or TensorRT
Experience with streaming or distributed data processing, such as Flink or Kafka
Solid grounding in evaluation, including building datasets, defining metrics, and detecting regressions
Familiarity with Kubernetes, Docker, and infrastructure as code, including Terraform and ArgoCD
AWS experience
Experience with the full computer vision data lifecycle is nice to have
Experience with auto-labeling or embedding-based data search is nice to have
Exposure to customer deployments or field-facing ML systems is nice to have

Benefits

Comp & perks

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
Daily meals in-office
Vibrant company events and team-building
401K retirement plan
HSA options
Pre-tax Commuter Card
Competitive salary
Dynamic work environment