Parallel
Senior Machine Learning/Computer Vision Engineer
Parallel, Los Angeles, California, United States, 90079
Senior Machine Learning/Computer Vision Engineer
Join to apply for the
Senior Machine Learning/Computer Vision Engineer
role at
Parallel . 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.
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 state-of-the-art methods as appropriate.
Build and contribute to infrastructure and tools for ML pipelines to automate data labeling, training workflows, evaluation processes, and model versioning.
Collaborate cross-functionally with other engineering, research, and product teams to ensure seamless integration of ML systems into real-world applications.
What Success Looks Like
After 30 Days: Develop a deep understanding of the current perception architecture, sensor setup, and system requirements; identify key ML-pipeline challenges and propose initial improvements.
After 60 Days: Lead design of a new or improved perception subsystem and contribute hands-on to ML-pipeline tooling; demonstrate early performance or reliability improvements.
After 90 Days: Deliver a perception feature with a working model in offline testing, integrated into the pipeline and progressing toward edge deployment with measurable gains.
Basic Requirements
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 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.
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.
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.
Compensation and Inclusion Target Salary Range:
$150,000—$240,000 USD
Parallel Systems is an equal opportunity employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to any discriminatory factor protected by applicable federal, state or local laws. We work to build an inclusive environment in which all people can come to do their best work.
Parallel Systems will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact your recruiter.
Job Details
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Engineering and Information Technology
Industries: Railroad Equipment Manufacturing
Note: This description reflects the current job and may be subject to change without notice.
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Join to apply for the
Senior Machine Learning/Computer Vision Engineer
role at
Parallel . 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.
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 state-of-the-art methods as appropriate.
Build and contribute to infrastructure and tools for ML pipelines to automate data labeling, training workflows, evaluation processes, and model versioning.
Collaborate cross-functionally with other engineering, research, and product teams to ensure seamless integration of ML systems into real-world applications.
What Success Looks Like
After 30 Days: Develop a deep understanding of the current perception architecture, sensor setup, and system requirements; identify key ML-pipeline challenges and propose initial improvements.
After 60 Days: Lead design of a new or improved perception subsystem and contribute hands-on to ML-pipeline tooling; demonstrate early performance or reliability improvements.
After 90 Days: Deliver a perception feature with a working model in offline testing, integrated into the pipeline and progressing toward edge deployment with measurable gains.
Basic Requirements
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 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.
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.
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.
Compensation and Inclusion Target Salary Range:
$150,000—$240,000 USD
Parallel Systems is an equal opportunity employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to any discriminatory factor protected by applicable federal, state or local laws. We work to build an inclusive environment in which all people can come to do their best work.
Parallel Systems will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact your recruiter.
Job Details
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Engineering and Information Technology
Industries: Railroad Equipment Manufacturing
Note: This description reflects the current job and may be subject to change without notice.
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