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 the United States, and who are prepared to travel to at least 2 in-person retreats per year.
About your role
As a Senior 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/CDsystems 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 $210K - $240K 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.
Originally posted on Himalayas