Voxel51

• Shape the architecture and evolution of Voxel51’s infrastructure to support deployments ranging from individual researchers to Fortune 500 enterprises • Design, build, and scale deployment systems across cloud (GCP, AWS, Azure) and on-premises environments, ensuring reliability, security, and repeatability • Partner with enterprise customers (and our Customer Success Machine Learning Engineers) to deliver and support production-grade deployments in their environments, guiding them through installation, troubleshooting, and scaling • Lead infrastructure initiatives across engineering teams, enabling peers to develop, test, and ship features faster with robust internal tooling and automation • Drive best practices in CI/CD, evolving our pipelines (currently GitHub Actions + Google Cloud Build) and introducing new approaches where they add value • Develop and maintain deployment solutions for Voxel51-hosted environments (GKE) as well as customer on-prem installations (K8s or Docker Compose) • Champion developer productivity, improving workflows for development and automated cloud deployments • Troubleshoot and resolve complex infrastructure issues, spanning build failures, runtime failures, and customer deployment challenges • Anticipate and prevent failures by designing monitoring, alerting, and predictive solutions for both internal and customer environments • Mentor engineers and set technical direction, ensuring Voxel51’s infrastructure remains ahead of customer needs and industry trends

First and most importantly: our mission is to bring transparency and clarity to the world's data. Our platform, FiftyOne, is where AI work happens. Our enterprise platform is the mission critical linchpin for managing unstructured data, model development, and AI systems at the world's largest companies. We believe that open source is the way to lead the data-centric AI revolution. Our open source version has 4 million downloads to-date. Our software massively impacts AI work across almost every vertical: from self-driving cars to medical imaging to revolutionizing agriculture, we are at the thrilling center of real-world AI advancement’s next wave. And we’re built on three key tenets: - We are all human beings: we strive to be a “human-first” organization and treat everyone with the respect, care, and flexibility that all people deserve. - We are distributed: we believe in getting autonomy and power into the hands of people actually doing the work. - We believe in the power of community. We are fully remote, hiring for people based in North America and who are prepared to travel to at least 2 in-person retreats per year. About your role As a Principal Infrastructure Engineer at Voxel51, you will shape the architecture and strategy of the systems that power our platform — from individual researchers to enterprise-scale deployments. You’ll lead the design of containerized systems, CI/CD pipelines, and deployment solutions across cloud and on-premises environments, while solving the unique challenges of serving unstructured data (images and video) at scale. You’ll partner with enterprise customers, guiding and troubleshooting their production deployments. You’ll collaborate across engineering teams to improve developer productivity, and mentor peers while setting infrastructure best practices. Your work will directly shape the reliability, security, and scalability of Voxel51’s platform — and accelerate our mission to democratize data-centric ML. What you will do - Shape the architecture and evolution of Voxel51’s infrastructure to support deployments ranging from individual researchers to Fortune 500 enterprises - Design, build, and scale deployment systems across cloud (GCP, AWS, Azure) and on-premises environments, ensuring reliability, security, and repeatability - Partner with enterprise customers (and our Customer Success Machine Learning Engineers) to deliver and support production-grade deployments in their environments, guiding them through installation, troubleshooting, and scaling - Lead infrastructure initiatives across engineering teams, enabling peers to develop, test, and ship features faster with robust internal tooling and automation - Drive best practices in CI/CD, evolving our pipelines (currently GitHub Actions + Google Cloud Build) and introducing new approaches where they add value - Develop and maintain deployment solutions for Voxel51-hosted environments (GKE) as well as customer on-prem installations (K8s or Docker Compose) - Champion developer productivity, improving workflows for development and automated cloud deployments - Troubleshoot and resolve complex infrastructure issues, spanning build failures, runtime failures, and customer deployment challenges - Anticipate and prevent failures by designing monitoring, alerting, and predictive solutions for both internal and customer environments - Mentor engineers and set technical direction, ensuring Voxel51’s infrastructure remains ahead of customer needs and industry trends What you should bring - Deep experience with containerized environments - Building, packaging, and debugging container images - Kubernetes (and Docker Compose) for orchestration - Building, maintaining, and deploying Helm charts - Infrastructure as Code expertise (Terraform, Ansible, or equivalent) - Scripting and automation skills (Bash or similar) - Python expertise, including build and environment management, packaging/distribution, release management, and dependency debugging - CI/CD systems experience, ideally GitHub Actions (we use this today) - Cloud infrastructure knowledge, especially GCP (IAM, VPC, load balancing, ingress/egress routing, proxies, firewall rules) - Database fundamentals, ideally MongoDB or similar NoSQL systems - Observability skills, including designing meaningful monitors, logging, tracing, and alerting - Security best practices, including certificates, service accounts, least privilege, and role assumptions - Troubleshooting ability across complex, distributed systems (including with customers in the loop) - Testing mindset: comfortable with designing and applying different types of tests to validate functionality - Strong communication skills, with the ability to work directly with enterprise customers as well as collaborate across teams in a remote-first, collaborative environment - Adaptability and curiosity, with the ability to ramp quickly on unfamiliar concepts and technologies The cash compensation for this person is in the $250K-$280K range. In addition to base comp for this role, we offer equity in the form of options, a variety of benefits, and the opportunity to grow in an exciting and collaborative environment.

• Shape the architecture and evolution of Voxel51’s infrastructure to support deployments ranging from individual researchers to Fortune 500 enterprises • Design, build, and scale deployment systems across cloud (GCP, AWS, Azure) and on-premises environments, ensuring reliability, security, and repeatability • Partner with enterprise customers to deliver and support production-grade deployments in their environments, guiding them through installation, troubleshooting, and scaling • Lead infrastructure initiatives across engineering teams, enabling peers to develop, test, and ship features faster with robust internal tooling and automation • Drive best practices in CI/CD, evolving our pipelines (currently GitHub Actions + Google Cloud Build) and introducing new approaches where they add value • Develop and maintain deployment solutions for Voxel51-hosted environments (GKE) as well as customer on-prem installations (K8s or Docker Compose) • Champion developer productivity, improving workflows for development and automated cloud deployments • Troubleshoot and resolve complex infrastructure issues, spanning build failures, runtime failures, and customer deployment challenges • Anticipate and prevent failures by designing monitoring, alerting, and predictive solutions for both internal and customer environments • Mentor engineers and set technical direction, ensuring Voxel51’s infrastructure remains ahead of customer needs and industry trends

• Work with users to identify best practices to implement their ML workflows • Run point on customer implementation, triaging bug reports, and day-to-day relationship management with users through channels like Slack, email, and weekly meetings • Generate training material and onboarding sessions and deliver them to users • Work with our product team to influence the roadmap and be the voice of the user within the organization • Contribute ML-specific features to our product, FiftyOne

• Collaborate with a team that delivers features to support dataset curation, model analysis, and integrations that span the entire machine learning lifecycle. • Build clean, scalable APIs and solve unique challenges that arise when working with unstructured data (images and video). • Contribute to a thriving open source community while also emphasizing enterprise-grade engineering for our commercial products. • Develop our open source SDK, as well as our enterprise APIs, UIs, and backend systems. • Help us scale our enterprise solution to support the largest vision AI datasets in existence, supporting individual researchers to Fortune 500 companies; processing petabytes of data. • Write production code that is maintainable, flexible, performant, and well tested. • Contribute to the department through tooling, automation, and best practices.

• Author original documentation, tutorials, guides, technical articles, and blogs • Code up integrations that combine FiftyOne with complementary ML technologies, models, and datasets • Self-produce short videos to supplement the written content • Provide technical answers to open source users on Discord, Stackoverflow, and Reddit • Create and deliver original courses, both online and in-person