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.
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

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.

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