ML Engineer for ETA Systems — Low-Latency, Scalable

United States Digital Space LLC; San Francisco (CA); Hybrid; USD 141,000 - 176,000; Full time

Benefits offered by this job

Medical insurance

Mental health benefits

Family building benefits

Child care

401(k) plan with company match

Paid time off

Parental leave

Commuter benefits

Company Pink membership

Job summary

United States Digital Space LLC is hiring a Machine Learning Engineer for our ETA system, which estimates and predicts ETAs for every ride request on our platform. ETAs influence matching decisions, pricing estimates and user experience, requiring low latency, high reliability and high accuracy.

You will work with engineers, ML and data science teams on rideshare experiences used by millions of riders and drivers. Our tech stack includes AWS, Kubernetes, Go, Spark, Python and Apache Airflow.

Qualifications

• 3+ years of machine learning experience.
• Experience with large-scale data processing and distributed data pipelines.
• Ability to work with cross-time-zone distributed teams.

Responsibilities

• Perform data analysis and build PoC to explore and compare ML and non-ML solutions.
• Make tradeoffs between model accuracy, production complexity and runtime performance.
• Develop statistical, machine learning, or optimization models.
• Write production quality code that can scale to millions of requests per day.
• Participate in code reviews, design reviews, and on-call incident triaging.
• Write well-crafted, readable, maintainable code.

Skills

Machine Learning

Distributed data pipelines

Data analysis

Cross-team collaboration

Education

B.S./M.S./Ph.D. in Computer Science or related field

Tools

AWS

Kubernetes

Go

Spark

Python

Apache Airflow

Job description

United States Digital Space LLC is hiring a Machine Learning Engineer for our ETA system, which estimates and predicts ETAs for every ride request on our platform. ETAs influence matching decisions, pricing estimates and user experience, requiring low latency, high reliability and high accuracy.

You will work with engineers, ML and data science teams on rideshare experiences used by millions of riders and drivers. Our tech stack includes AWS, Kubernetes, Go, Spark, Python and Apache Airflow.