Machine Learning Engineer

About Loop

Loop's mission is to simplify logistics payments. Loop is a connected finance platform 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 4% 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 Index Ventures, 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.

Techcrunch article about Loop.

About You

In this role, you would be responsible for building the foundational Machine Learning infrastructure. Your first focus would be leveraging NLP/CV techniques to digitalize and understand documents. You would also extend the machine learning platform to other areas,. This is a green field project, so you would have the opportunity to architect the machine learning system from scratch! You'll be working closely with our CTO and Customer Success team on this key initiative for the company.

Responsibilities

• Build end-to-end machine learning projects from ideation to production
• Design and implement data infrastructure to apply CV/NLP techniques to extract and normalize document data.
• Work closely with the engineering team for deploying and monitor deep learning models
• Measure and improve human-in-the-loop annotation data quality
• Research the state-of-the-art scientific literature in information extraction for a better understanding of all types of complex documents
• Prototype and develop algorithms using advanced deep learning techniques for document understanding
• Extend machine learning platform to other areas, such as workflow automation, fraud detection, risk evaluation

Qualifications

• 1+ years of hands-on professional experience in designing and building production-grade solutions in one or more of the following areas: Optical character recognition, named entity recognition, document classification, key information extraction, document layout analysis, document question answering, table detection
• 1+ years of hands-on experience in deep learning frameworks (e.g., PyTorch, Tensorflow, etc.)
• Experience in implementing state-of-the-art products in neural networks using CNN, LSTM-RNN, Transformer, or similar
• Experience in cloud environments (AWS, Google, Azure)
• Proficient in Python

Bonus points

• 3+ years of experience with NLP models and libraries such as Huggingface, BERT, GPT, etc. is a plus
• 5+ years of experience in computer vision is a plus
• Relevant PhD or master's degree is a plus

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