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MTS - Infrastructure

Join Omnifold's Infrastructure Team to build robust systems for AI model training and deployment in a fast-paced environment.

Location
San Francisco HQ
Compensation
Not disclosed
Level
mid
Type
full time · On-site

Posted by employer 6 months ago

First seen on Joblaze 1 week ago

Last verified on the company career page 1 day ago

Apply at Omnifold → Save job Scanned from omnifold.ai

Skills & Technologies

AWS Python Flexible on stack

AI in the day-to-day

We train custom AI models for forecasting, requiring unique infrastructure for model training and inference.

Requirements

Education
Bachelor's degree

Not disclosed in this posting: compensation, years of experience, visa sponsorship.

Joblaze summary

In this role, the individual will focus on developing and maintaining the infrastructure that supports the deployment and monitoring of custom AI models for forecasting. Key skills include expertise in cloud computing, particularly with GPU workloads, and proficiency in Python, alongside a solid understanding of security practices and CI/CD processes. This position is ideal for someone with a strong computer science background who thrives in a fast-paced environment and is eager to engage with unique machine learning workflows. Omnifold's Infrastructure Team plays a crucial role in ensuring the reliability and efficiency of their innovative AI-driven solutions.

Joblaze insights

Quick facts

Is the MTS - Infrastructure role remote?
No — this is an on-site role in San Francisco HQ.
Where is the role based?
Omnifold is hiring for this position in San Francisco HQ.
What's the tech stack?
Joblaze extracted these technologies from the posting: AWS, Python.
What seniority level is this role?
Omnifold targets mid-level candidates for this position.
Is this full-time or contract?
Full-time for this MTS - Infrastructure role at Omnifold.

From the original posting

Infrastructure Team

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.

What makes this job interesting:

  • 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.

What you’ll own

  • 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

What we’re looking for

  • 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)

Omnifold’s Mission

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.

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