ML / Computer Vision Engineer

Job Description

Job Description

Title : Senior Machine Learning / Computer Vision Engineer

Type : Full-Time + Remote

Compensation Range : $150,000 – $240,000 USD

Location : Los Angeles, CA, United States

Work Schedule : Full-Time, U.S. Time Zone

Industry : Autonomous Transportation Technology

Work Authorization : Must be authorized to work in the United States. No visa sponsorship is available for this role.

Company Overview

The organization operates in the autonomous transportation sector, developing battery-electric rail vehicles designed to modernize freight logistics. Its mission centers on improving safety, efficiency, and environmental impact by shifting portions of long-haul freight movement from road to rail through advanced autonomous systems. The company is in a growth phase, building next-generation technology for large-scale, real-world deployment.

Position Summary

The Senior Machine Learning / Computer Vision Engineer will lead the development of perception systems that enable fully autonomous, battery-electric rail vehicles to safely and reliably operate in complex real-world environments. This role focuses on designing, training, and deploying deep learning models that interpret multimodal sensor data and support real-time decision-making in safety-critical conditions. The position requires strong technical ownership, from early system design through production deployment, and close collaboration with cross-functional engineering teams.

Key Responsibilities

• Design, develop, and deploy advanced machine learning models for large-scale perception problems.
• Demonstrated hands-on 0 to 1 builds of perception systems,
• Own the full machine learning lifecycle, including data mining, annotation strategies, model training, evaluation, and deployment.
• Build and optimize deep learning architectures for object detection, segmentation, tracking, pose estimation, and scene understanding.
• Develop scalable training pipelines and ensure models meet real-time inference and reliability requirements.
• Work extensively with large-scale image, video, lidar, and radar datasets to support autonomous perception systems.
• Conduct research and empirical evaluations of new architectures and algorithms, adapting state-of-the-art techniques where appropriate.
• Contribute to infrastructure and tooling for automated data labeling, training workflows, evaluation, and model versioning.
• Collaborate with autonomy, robotics, systems, and product teams to integrate perception models into production systems.

Required Qualifications

Preferred Qualifications