JOB DESCRIPTION

Title: Senior Machine Learning / Computer Vision Engineer

Type: Full-Time

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

Location: Remote — 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.
• 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

• Bachelor’s degree or higher in Computer Science, Machine Learning, or a related technical discipline.
• Four or more years of experience developing and deploying machine learning systems at scale.
• Strong background in computer vision and deep learning with real-world application experience.
• Proficiency in Python and common scientific computing libraries.
• Expertise in at least one deep learning framework such as PyTorch or TensorFlow.
• Strong foundation in linear algebra, probability, geometry, and optimization.
• Demonstrated ability to work independently and drive complex technical projects.
• Strong communication skills and experience collaborating across disciplines.

Preferred Qualifications

• Experience with multimodal perception and sensor fusion using cameras, lidar, and radar.
• Experience optimizing models for edge deployment with real-time constraints.
• Background in autonomous systems, robotics, or other safety-critical domains.
• Publications in top-tier machine learning or computer vision conferences.
• Experience with GPU acceleration, CUDA, or inference optimization tools.
• Knowledge of low-level programming languages such as C++ or Rust.
• Experience working directly with sensing hardware and understanding sensor limitations.