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Full-Time

Senior Machine Learning Engineer

Confirmed live in the last 24 hours

Metropolis

Metropolis

201-500 employees

Computer vision-based parking and payment solutions

Data & Analytics
Fintech
AI & Machine Learning
Financial Services
Real Estate
Consumer Goods

Compensation Overview

$170k - $210kAnnually

+ Bonus + Stock Options + Healthcare Benefits + 401(k) Plan + Disability Coverage + Life Insurance

Mid, Senior

Seattle, WA, USA

Category
Applied Machine Learning
AI & Machine Learning
Required Skills
Microsoft Azure
Python
Data Structures & Algorithms
SQL
AWS
Google Cloud Platform
Requirements
  • PhD (strongly preferred) or MS in Operations Research, Statistics, Economics, Computer science or a relevant quantitative discipline.
  • 4+ years of industry experience as a ML scientist, research engineer, or equivalent role.
  • Strong proficiency in Python and SQL for model development and statistical analysis.
  • Proven expertise in implementing and deploying machine learning algorithms related to optimization and forecasting.
  • Experience with large-scale datasets, data warehouses, ETL pipelines, and familiarity with relevant tools and libraries.
  • Proficiency with optimization libraries such as SciPy, CVXPY, or Gurobi.
  • Proficiency in utilizing cloud platforms such as AWS, Azure, or GCP.
  • Previous experience working inside innovative, high-growth environments.
  • A proven track record of publications in machine learning or optimization conferences and journals (ICML, ICLR, Neurips, INFORMS, SIAM, etc).
Responsibilities
  • Research and develop optimization, machine learning, and statistical models to solve complex pricing challenges.
  • Navigate large and complex datasets to derive insights that inform key algorithmic strategies for pricing.
  • Shepherd models and algorithms from conception to production, ensuring successful and sustainable deployments.
  • Communicate ideas and results effectively, verbally and in writing, to a wide range of technical and non-technical audiences.
  • Collaborate closely with cross-functional teams to ensure alignment with organizational objectives and requirements.

Metropolis utilizes computer vision and machine learning to revolutionize parking, eliminating the need for cash, credit cards, or tickets. The company is also exploring technology for enabling "checkout-free" experiences in physical spaces, enhancing the overall parking and payment experience.

Company Stage

Series C

Total Funding

$1.9B

Headquarters

Santa Monica, California

Founded

2017

Growth & Insights
Headcount

6 month growth

13%

1 year growth

21%

2 year growth

30%
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Simplify's Take

What believers are saying

  • The acquisition of SP Plus Corporation for $1.5 billion could significantly expand Metropolis's market reach and operational capabilities.
  • Raising over $107 million in new equity investment highlights investor confidence and provides ample resources for innovation and expansion.
  • Metropolis's AI-driven approach to parking management offers employees the opportunity to work on cutting-edge technology in a growing industry.

What critics are saying

  • The competitive landscape, including established players like ParkMobile, poses a challenge to Metropolis's market penetration.
  • Rapid expansion and large acquisitions may strain Metropolis's operational and integration capabilities.

What makes Metropolis unique

  • Metropolis leverages AI and computer vision to offer checkout-free payment experiences, setting it apart from traditional parking solutions.
  • The company's focus on AI-powered parking infrastructure provides a modern, tech-driven alternative to competitors like ParkMobile.
  • Significant funding rounds, including a recent $167 million investment, underscore Metropolis's strong financial backing and growth potential.