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.