AI Infrastructure Engineer
San Francisco, CA, United States
About Loop
Loop is on a mission to unlock profits trapped in the supply chain (https://loop.com/article/unlock-profit-trapped-in-your-supply-chain) and lower costs for consumers. Bad data and inefficient workflows create friction that limits working capital and raises costs for every supply chain stakeholder.
Loop’s modern audit and pay platform uses our domain-driven AI to harness the complexity of supply chain data and documentation. We improve transportation spend visibility so companies can control their costs and power profit. That is why industry leaders like J.P. Morgan Chase, Great Dane, Emerge, and Loadsmart work with Loop.
Our investors include J.P. Morgan, Index Ventures, Founders Fund, 8VC, Susa Ventures, Flexport, and 50 industry-leading angel investors. Our team brings subject matter expertise from companies like Uber, Google, Flexport, Meta, Samsara, Intuit, Rakuten, and long-standing industry leaders like C.H. Robinson.
About You
You will be the first AI Infra engineer at Loop. You will lay the foundation of AI Infrastructure at Loop from scratch. Your first focus is automating and scaling the model training process. Loop saw a 100X growth in AI model usage in 2023 and expects a 20X growth in Q1 based on signed clients. Your work will help Loop meet unprecedented demands on AI models that extract, normalize, assign and link logistics documents. You will unlock different vectors of professional growth, leading Loop’s AI Infra, building more AI powered products or owning overall Loop infrastructure.
Responsibilities
Design and build end-to-end AI model training pipeline includes: data ETL of unstructured data, and automated GPU training.
Automated reliable model training on remote GPUs.
Design and build a model management system for deploying, monitoring, and potentially rolling back new models.
Design and build an observability framework that monitors the performance of models in performance.
Work closely with the AI engineering team for deploying and monitoring production models.
Measure and improve human-in-the-loop annotation data quality.
Qualifications
2+ years of hands-on experience in deep learning frameworks (e.g., PyTorch, Tensorflow, etc.).
Experience with Python, Docker, Kubernetes, and Infrastructure as Code, CI/CD pipelines and monitoring tools.
Experience managing, scaling and monitoring clusters in production.
Ability to design software and systems and ship high-quality code to production.
Experience in cloud environments (AWS, Google, Azure).
Compensation
Base pay 120k - 190k
Benefits & Perks
Premium Medical, Dental, and Vision Insurance plans
Insurance premiums covered 100% for you
Unlimited PTO
Fireside chats with industry leading keynote speakers
Off-sites in locales such as Napa and Tahoe
Generous professional development budget to feed your curiosity
Physical and Mental fitness subsidies for yoga, meditation, gym, or ski memberships
Why you should join Loop? - https://whyyoushouldjoin.substack.com/p/loop
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