Parallel Systems is pioneering autonomous battery-electric rail vehicles designed to transform freight transportation by shifting portions of the $900 billion U.S. trucking industry onto rail, and is seeking a Senior Machine Learning/Computer Vision Engineer to help build the next generation of perception systems powering their fully autonomous vehicles.
Requirements
- Strong background in computer vision and/or deep learning with practical experience in designing and training neural networks for real-world applications.
- Proficiency in Python and familiarity with standard ML libraries and tools (e.g., NumPy, SciPy, Pandas).
- Expertise in at least one deep learning framework such as PyTorch or TensorFlow.
- Strong mathematical foundation in linear algebra, geometry, probability, and optimization.
- Experience with multi-modal perception (e.g., sensor fusion from cameras, lidar, radar).
- Experience optimizing models for deployment on edge devices with real-time constraints.
- Background in autonomous systems, robotics, or other safety-critical domains.
Responsibilities
- Design, develop, and deploy advanced machine learning models for large-scale perception problems.
- Own the full ML lifecycle—from data mining and annotation to training, evaluation, and deployment of production-grade models.
- Build and optimize deep learning architectures for object detection, segmentation, tracking, pose estimation, and scene understanding.
- Develop scalable and efficient training pipelines that ensure robust, real-time inference performance.
- Work extensively with large image, video, lidar and radar datasets to power next-generation computer vision systems.
- Conduct research and empirical studies to evaluate new architectures, techniques, and algorithmic improvements, incorporating or adapting state-of-the-art methods as appropriate.
- Build and contribute to infrastructure and tools for supporting ML Pipeline to automate data labeling, training workflows, evaluation processes, and model versioning.
Other
- Bachelor’s or higher degree in Computer Science, Machine Learning, or a related technical discipline.
- 4+ years of hands-on experience developing and deploying ML systems at scale.
- Proven track record of working autonomously and driving complex technical projects in fast-paced environments.
- Excellent communication and collaboration skills, with experience working on interdisciplinary teams.
- Commitment to providing fair and transparent compensation in accordance with applicable laws.
