Machine Learning Engineer

Loop
·
Posted: 
June 1, 2023
·
Onsite
Job Commitment
Full-time
Job Commitment
Mid Level
Job Function
Dev & Engineering
Salary
N/A
Job Commitment
Full-time
Experience Level
Mid Level
Workplace Type
Onsite
Job Function

This job is closed

We regret to inform you that the job you were interested in has now been closed. Although this specific position is no longer available, we encourage you to continue exploring other opportunities on our job board.

About the position

In this role, you will be responsible for building the foundational Machine Learning infrastructure and leveraging NLP/CV techniques to digitalize and understand documents. You will have the opportunity to architect the machine learning system from scratch and work closely with the CTO and Customer Success team. Your main responsibilities will include building end-to-end machine learning projects, designing and implementing data infrastructure, deploying and monitoring deep learning models, improving data quality, researching scientific literature, and developing algorithms for document understanding. Additionally, you will have the opportunity to extend the machine learning platform to other areas such as workflow automation, fraud detection, and risk evaluation.

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

Requirements

  • 1+ years of hands-on professional experience in designing and building production-grade solutions
  • Experience in leveraging NLP/CV techniques to digitalize and understand documents
  • Knowledge of data infrastructure design and implementation for applying CV/NLP techniques to extract and normalize document data
  • Ability to work closely with the engineering team for deploying and monitoring deep learning models
  • Proficiency in measuring and improving human-in-the-loop annotation data quality
  • Familiarity with the state-of-the-art scientific literature in information extraction for a better understanding of complex documents
  • Experience in prototyping and developing algorithms using advanced deep learning techniques for document understanding
  • Ability to extend machine learning platform to other areas, such as workflow automation, fraud detection, and risk evaluation

Benefits

  • 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

Job Application Resources

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Loop

Loop develops a logistics payments platform that ingests data and streamlines shipment document capture.
Location
San Francisco, CA
Company Size
Workplace Type
Industries
FinTech
Information Technology
Logistics
Payments
Financial Services
Transportation
Open Roles
9
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Loop

Loop develops a logistics payments platform that ingests data and streamlines shipment document capture.
Company Overview

Loop develops a logistics payments platform that ingests data and streamlines shipment document capture.

Benefits
  • Simplify logistics payments
  • Connected finance platform
  • Frictionless payments for logistics industry
  • Eliminate billing and payment errors
  • Spend 4% less and increase back office productivity by 80%
  • Product-obsessed team
  • Investors include Index Ventures, Founders Fund, 8VC, Susa Ventures, Flexport, and 50 industry-leading angel investors
  • Team made up of talented individuals from technology companies like Uber, Google, Flexport, Intuit, and Rakuten, as well as traditional logistics companies like CH Robinson
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