Staff ML Engineer: Build Scalable Data Flywheel & Infra

Deepstreamtech; San Francisco (CA); Hybrid; USD 120,000 - 150,000; Full time

Job summary

Deepstreamtech in San Francisco is hiring an experienced software engineer specializing in machine learning infrastructure. In this hybrid role, you'll work with the Perception team to develop scalable ML systems integrated into autonomous vehicle technology, processing vast amounts of data efficiently.

Applicants should have a strong background in C++ and Python, along with over 4 years of experience in software engineering and machine learning. Position emphasizes building cutting-edge ML data infrastructure and collaboration with research teams.

Qualifications

• 4+ years of professional experience in software engineering and machine learning.
• Experience in designing distributed systems processing data at scale.
• Good foundational understanding of ML principles and SOTA methods.

Responsibilities

• Build the system that learns spatial-temporal representation for an autonomously driving vehicle.
• Conduct research for real-world problems and collaborate with research teams.
• Develop methods for efficiently and continuously learning from large scale real-world data.
• Design scalable infrastructure solutions that support model improvement.
• Collaborate with ML infrastructure teams to address issues.

Skills

C++

Python

Machine Learning

Distributed Systems

Data Compliance

Data Governance

Communication Skills

Education

Degree in Computer Science, Engineering or related field

Job description

Deepstreamtech in San Francisco is hiring an experienced software engineer specializing in machine learning infrastructure. In this hybrid role, you'll work with the Perception team to develop scalable ML systems integrated into autonomous vehicle technology, processing vast amounts of data efficiently.

Applicants should have a strong background in C++ and Python, along with over 4 years of experience in software engineering and machine learning. Position emphasizes building cutting-edge ML data infrastructure and collaboration with research teams.