About Loop

Loop's mission is to simplify logistics payments. Loop is building modern economic infrastructure to enable frictionless payments for one of the world's largest industries – logistics. Shippers, carriers, and 3pls that onboard to Loop eliminate painful billing and payment errors – resulting in spending 3% less and an 80% increase in back-office productivity. Loop's new logistics payment platform won’t just change how people pay. It’s going to fundamentally move logistics forward.

Loop has a product-obsessed team that enjoys building core infrastructure that impacts everyone. Investors include JPMC, Index, Founders Fund, 8VC, Susa Ventures, Flexport, and 50 industry-leading angel investors. The team is made up of talented individuals from technology companies like Uber, Google, Flexport, Intuit, and Rakuten – as well as traditional logistics companies like CH Robinson.

Why you should join Loop

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, and 
• 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