Infrastructure Engineer, Voxel51
$195-220k
+ Equity in the form of options
Data platform for computer vision models
Job no longer available
Data platform for computer vision models
21-100 employees
Job no longer available
$195-220k
+ Equity in the form of options
21-100 employees
Company mission
Voxel51's mission is to bring transparency and clarity to the world's data through its computer vision data modelling platform.
Role
Who you are
- 7+ years of professional experience managing and deploying software systems
- Expertise with containerization and container orchestration (Docker, Kubernetes)
- Experience with infrastructure automation
- We use Terraform and Ansible, but bringing other technologies to the table is GREAT!
- Scripting (Bash) and Software Languages (Python, Go)
- Test Driven Development (TDD) with pytest and Terratest
- Management of NoSQL databases (MongoDB, DocumentDB, Elasticsearch)
- Observability (metrics, monitoring, alerting, dashboarding, logging)
- Software packing (Python Wheels, PyPI), container image building, and release management
- Security with experience applying the Principle of Least Privilege
- Continuous Integration (CI) and Continuous Delivery (CD) systems
- We use Google Cloud Build and GitHub Actions, but experience with other technologies is great!
- Networking, Access Control Lists (ACLs), Load Balancers, DNS, TLS, Webservers (Nginx)
- Linux (Debian based distributions)
- Documentation generation and curation (internal and customer facing)
- Experience working with enterprise customers to deploy containerized systems into their environments (AWS, GCP, Azure, on-premises)
- Ability to work in a remote-first, cooperative environment using collaborative development tools (GitHub, Slack)
What the job involves
- As a Senior Infrastructure Engineer at Voxel51, you’ll collaborate with a team that delivers features to support dataset curation, model analysis, and integrations that span the entire machine learning lifecycle
- You’ll design and develop containerized systems and CI/CD pipelines using industry best-practices that deploy software in our cloud and into our customers’ environments
- You’ll also solve unique challenges that arise when storing, managing, and serving unstructured data (images and video) at scale
- Design, develop, and manage systems that leverage best-of-breed tools like Docker and Kubernetes to deploy and scale from individual users to Fortune 500 companies
- Build and maintain robust CI/CD pipelines
- We use GitHub Actions and Google Cloud Build right now, but we'd definitely be open to other answers!
- Work with enterprise customers to deploy into, troubleshoot and manage their cloud or on-premises environment installations
- Collaborate with Customer Success machine learning engineers during customer acquisition lifecycle
- Deploy and manage Voxel51-hosted, customer environments using GKE and MongoDB
- Create and maintain deployment solutions for customers' on-prem deployments
- We use Helm and Docker Compose, but other answers would be AWESOME!
- Design, develop, and manage solutions for improving efficiency in peer Engineering organizations
- Local deploys (using minikube and skaffold now, other tools would be awesome)
- Automated deploys to cloud (GKE) environments
- Automated deploys to internal Docker Compose environments
- Troubleshoot deployment failures, build failures, runtime failures
- Design, develop, and manage solutions to predict failures in internal and customer installations
Our take
Recent innovations in computer vision mean that AI can recognise images within large-scale datasets, presenting significant opportunities for innovation in just about every industry. However, this only works successfully when AI is trained with high-quality datasets, and it is difficult to organize, locate, and correct mistakes at such high scale.
Voxel51 provides a data platform for computer vision models called FiftyOne, an open-source toolkit that helps users automate the organization, navigation, and creation of computer vision models, regardless of size. The platform also includes automated data quality control tools to help users identify detrimental mistakes within models, a process that is necessary for successful computer vision.
Many startups are tackling inefficient computer vision workflows, but Voxel51 has found a gap in the market by focusing specifically on the laborious manual processes associated with organising and aggregating high-quality datasets. It has formed a collaborative partnership with Google, empowering its platform with Google's pre-annotated image datasets, and in 2023, released an AI assistant that can generate Python Code for computer vision dataset analysis. 2024 funding is being used to scale up and accelerate its AI research.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 4 rounds)
May 2024
$30m
SERIES B
Sep 2022
$12.5m
SERIES A
Total funding: $45.8m
Company benefits
- Medical, Dental & Vision
- Flexible work schedules
- Generous PTO
- Family-friendly policies
- Stock options
- 401k matching
- Flexible set-up
- Rich team building
- Healthy remote playbook
Company HQ
Ann Arbor, MI
Leadership
Jason Corso
(Co-Founder & Chief Science Officer)Experience as Director of the Stevens Institute for Artificial Intelligence. Associate Professor of Electrical Engineering and Computer Science at the University of Michigan since 2014.
Brian Moore
(Co-Founder & CEO)Was a Software Engineering and Research Intern at Google. Also a Graduate Research Assistant at the University of Michigan from 2012 to 2017.
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