Senior Machine Learning/Computer Vision Engineer

Position Overview

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. Our innovative technology offers cleaner, safer, and more efficient logistics solutions. Join our dynamic team and help shape a smarter, greener future for global freight.

Senior Machine Learning/Computer Vision Engineer: Parallel Systems is seeking an experienced Machine Learning Engineer to help build the next generation of perception systems powering our fully autonomous, battery-electric rail vehicles. In this role, you'll take ownership of designing and deploying cutting-edge deep learning models that enable our vehicles to perceive and reason about complex, real-world environments. You'll collaborate closely with top-tier engineers across autonomy, robotics, and systems, tackling some of the most challenging problems in real-time machine learning and computer vision. This role requires at least one week a month in our LA office.

Key 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 pipelines to automate data labeling, training workflows, evaluation processes, and model versioning.
• Collaborate cross-functionally with engineering, research, and product teams to ensure seamless integration of ML systems into real-world applications.

Required Qualifications

• 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.
• Strong background in computer vision and/or deep learning with practical experience 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.
• Proven track record of working autonomously and driving complex technical projects in fast-paced environments.
• Excellent communication and collaboration skills with experience on interdisciplinary teams.

Preferred Qualifications

• 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.
• Publications in top-tier ML or CV conferences (e.g., CVPR, ICCV, NeurIPS, ICML, ECCV).
• Experience with GPU/TPU programming and optimization tools (e.g., CUDA, TensorRT).
• Knowledge of low-level programming languages like C++ or Rust.
• Experience working directly with sensing hardware and understanding its constraints.