Voxel

Full-stack Engineer

• Build and ship features across our web dashboard and (later) our React Native mobile app.
• Contribute to high-impact roadmap initiatives including:
• Executive Hub – global multi-facility operational visibility for enterprise leaders.
• Snapshots – proactive, subscription-based safety insights (e.g., PPE compliance, collision risk, hotspot detection).
• Own parts of the application layer: APIs, data modeling, authentication, authorization, and UI behaviors.
• Collaborate with CV/ML & Platform Engineering
• Work with perception teams to understand AI outputs, define interface requirements, and ensure the right data is available to power new features.
• Troubleshoot and triage issues that require application + CV/ML context (e.g., mislabeled signals, missing detections, unexpected data patterns).
• Support scaling to new customer sites by integrating CV outputs into the application layer and validating customer-facing behavior.
• Partner with Product, Design, Sales Engineering, and Customer Success to shape solutions for complex enterprise workflows.
• Surface edge cases, system failures, and user-impacting issues, and collaborate with engineering teams to drive resolution.
• Participate in cross-functional discussions on how to best present safety insights, model outputs, time-series data, and corrective actions.

Software Engineer – Applications L3/L4

Sales

• Drive new business development efforts, cultivating relationships with enterprise prospects and strategic accounts.
• Own and expand high-value ICP inbound opportunities and priority enterprise targets.
• Lead account mapping and multi-threaded pursuit strategies to drive enterprise penetration.
• Build and nurture strong champions across client organizations—including influential stakeholders and C-suite executives—to accelerate deal velocity and ensure long-term account growth.
• Leverage Salesforce to manage pipeline, forecast performance, and guide decision-making.
• Maintain consistent and proactive communication throughout the entire sales cycle.
• Monitor and synthesize industry trends to inform go-to-market strategy in a dynamic, competitive landscape.

Sales Director – Enterprise

Sales Development Rep

• Educate the Market–Most companies don’t realize AI can prevent injuries. You’ll be the first to tell them.
• Own outbound prospecting—research, identify, and engage key prospects to build a high-value sales pipeline.
• Break through the noise—use creative, multi-channel outreach (cold calls, emails, LinkedIn) to grab attention and drive conversations.
• Engage top decision-makers—connect with leaders in safety, operations, and risk management to uncover pain points and spark interest.
• Collaborate closely—partner with Account Executives to set up high-quality first meetings.
• Optimize & improve—analyze your outreach performance, track your success, and tweak your approach to keep winning.

Sales Development Representative

• Design, build, and scale core components of Voxel’s perception and computer vision systems, enabling real-time understanding of safety and operations in industrial environments
• Lead the development of distributed systems for ingesting, processing, and analyzing video data across edge devices and cloud infrastructure
• Develop secure, scalable backend services and APIs to power our video platform, including access control, data pipelines, and event detection services
• Contribute to the architecture of low-latency, resilient services supporting real-time alerts, historical analytics, and ML inference workflows
• Partner with ML engineers, product managers, and platform teams to deploy and operationalize machine learning models in production
• Take ownership of key technical areas, influence design decisions, and mentor junior engineers when needed
• Uphold engineering best practices in code quality, testing, monitoring, and operational excellence

Senior/Staff Software Engineer - Platform

DevOps Engineer

• Build and maintain cloud infra and distributed systems for data processing, MLOps and other services.
• Develop and implement DevOps practices to deploy applications in AWS EKS.
• Build infrastructure configuration-as-code modules using Terraform.
• Design and develop architectures for running AI on realtime video at scale.
• Implement security best practices for the software engineering organization.

Senior Software Engineer – DevOps

• Contribute to the development and scaling of Voxel’s perception and computer vision systems, powering real-time understanding of industrial environments
• Design and deploy distributed systems for video ingestion, processing, and inference across both edge devices and cloud infrastructure
• Build and secure cloud APIs, access control systems, and backend services that support the video platform and data pipelines
• Develop scalable and resilient services that enable low-latency event detection, real-time alerts, and historical video analytics
• Collaborate with cross-functional teams—including ML engineers, product managers, and researchers—to bring computer vision models into production
• Influence the team’s technical direction and uphold high standards in code quality, system design, and operational excellence

Software Engineer – Platform

Research Scientist

• Lead State-of-the-Art Research: Invent and implement computer vision and generative AI algorithms that push the boundaries of the field. Stay abreast of the latest advances in deep learning, visual reasoning, and large-scale data processing
• Design Scalable Real-Time Systems: Create models that can reliably handle input from thousands of always-on video cameras, running at scale 24/7, and extract actionable insights around safety issues
• Collaborate with Cross-Functional Teams: Work closely with software engineering, cloud, and ML operations teams to optimize data ingestion, model retraining, and redeployment flows across large-scale infrastructures
• Consult on Customer Solutions: Advise Sales, Customer, and Field Engineering teams in defining and customizing solutions to meet complex client requirements
• Contribute to Product Evolution: Transfer research findings into production, contributing to the continuous improvement of our cutting-edge platform
• Drive Continuous Innovation: Shape Voxel’s vision for deploying generative AI to solve industrial and enterprise-scale computer vision problems, using millions of videos to find patterns and deliver actionable insights to customers.

Senior Research Scientist, Computer Vision, Generative AI

• Lead from the Front – Prospect alongside your team to model best practices and set the pace for outbound activity.
• Drive Pipeline Growth – Ensure the team consistently delivers high-quality meetings and opportunities for Account Executives.
• Establish KPIs – Create clear, data-driven performance metrics (activity levels, conversion rates, pipeline goals) and manage to them rigorously.
• Coach & Develop – Provide ongoing 1:1 coaching, call reviews, and training to uplevel performance.
• Enforce Accountability – Foster a results-driven culture with transparency on metrics and outcomes.
• Optimize Playbooks – Continuously refine outreach strategies, messaging, and cadences to improve conversion rates.
• Hire & Scale – Recruit and onboard top BDR talent as the team expands.
• Cross-Team Collaboration – Partner closely with Marketing and Sales leadership to align pipeline strategy with revenue objectives.

Sales Manager – Player-Coach

Machine Learning Engineer

• 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.