
Omnifold trains custom AI models that help planners forecast the future. We are hiring for our Infrastructure Team, who own the systems that make everything else possible.
We train a unique model for each customer, which means model training and inference work differently here than at any other company. You’ll never get more reps building model training infrastructure!
Our team has very fast iteration speed but needs robust monitoring to pick up signal on user patterns. This is especially important as our application interface for AI-driven forecasting is unique on the market.
Deployment: Reliable processes for getting models and services into production
Security: Data isolation between customers, product security, infrastructure hardening (SOC2 compliance and beyond)
Cloud resource management: GPU allocation, instance sizing, cost optimization
Monitoring and logging: Visibility into what's running, what's failing, and why
Data and ML ops: ETL pipelines from varied customer data sources, model versioning and lifecycle management
Automated testing: Building the test infrastructure that lets us ship with confidence
Experience with cloud computing (especially GPU workloads), CI/CD infrastructure-as-code. We run on AWS
Familiarity with or interest in ML workflows
Security fundamentals: encryption, access controls, compliance basics
Python proficiency
Must have a strong Computer Science background
Location: San Francisco (in-person, 5 days per week)
Every bad forecast has a physical consequence. Unnecessary goods are manufactured, shipped, and stored. Emergency air freight is needed for misallocated products. Poor production planning means workers show up with nothing to do, or work frantic overtime. Inefficiency is everywhere.
Our mission is to eliminate waste and accelerate growth for every company with physical products.
Compensation: $150K to $300K base | Equity | Health, dental, vision | 401(k)
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