Parallel LLC jobs in Los Angeles, CA - 5 jobs

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 Controls Engineer Parallel is seeking a Senior Controls Engineer with deep expertise in control systems development to join our engineering team. This role focuses on designing, developing, and implementing robust software that controls the electrical and mechanical systems on our rail vehicles. The ideal candidate has a strong foundation in control systems theory, experience with real-world hardware integration, and a proven track record of delivering high-quality, real-time control software. Responsibilities: Design and implement control algorithms for embedded systems and hardware platforms Determine sensor and actuator requirements to meet system performance needs Perform modeling, simulation, and analysis of dynamic systems using tools such as MATLAB/Simulink Support system integration, bring-up, and debugging of software-hardware interactions, including live testing in the field Ensure high reliability, safety, and performance in all control software implementations Contribute to software architecture and long-term technical direction of the software stack Provide technical leadership and mentorship within the team Basic Requirements: Bachelor's or Master's degree in Electrical Engineering, Mechanical Engineering, Software Engineering, Mathematics, or a related field 5+ years of experience developing control software for embedded systems or hardware platforms Professional experience and understanding of control theory, including PID, state-space, observers, and system dynamics Proficiency in C/C++, Python, or similar languages used in embedded systems development Professional experience with development tools such as MATLAB, Simulink, and hardware-in-the-loop (HIL) testing Preferred Qualifications: Hands-on experience with embedded platforms (e.g., ARM Cortex, DSPs, RTOS-based systems) Exposure to the automotive, aerospace, or robotics industries Experience developing with Rust, especially in embedded platforms Experience with sensor fusion, motion control, braking systems, or electric powertrains Prior ownership of a systems project from design through implementation, testing and deployment in the field We are committed to providing fair and transparent compensation in accordance with applicable laws. Salary ranges are listed below and reflect the expected range for new hires in this role, based on factors such as skills, experience, qualifications, and location. Final compensation may vary and will be determined during the interview process. The target hiring range for this position is listed below. Target Salary Range:$175,000-$215,000 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 is committed to the full inclusion of all qualified individuals. As part of this commitment, 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.

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. From handling adverse weather and ambiguous signals to navigating multi-agent interactions on active railways, your work will directly shape the safety and reliability of our autonomous platform. 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. If you're excited by the opportunity to push the boundaries of AI in safety-critical, real-world applications, we'd love to work with you. This role requires at least one week a month or more in our LA office per month. 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. 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: You have developed a deep understanding of the current perception architecture, sensor setup, and system requirements. You've identified key challenges in the ML pipelines and proposed initial areas for improvement across data workflows, model performance, and deployment constraints. After 60 Days: You've led the design of a new or improved perception subsystem and contributed hands-on to ML pipeline tooling. You've built a proof of concept aligned with system needs, demonstrating early improvements in performance or reliability based on real-world constraints. After 90 Days: You have delivered a perception feature with a proven working model in offline testing, showing measurable gains. The system is integrated into the pipeline and is progressing toward edge deployment, with a clear impact on overall perception capabilities. 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. We are committed to providing fair and transparent compensation in accordance with applicable laws. Salary ranges are listed below and reflect the expected range for new hires in this role, based on factors such as skills, experience, qualifications, and location. Final compensation may vary and will be determined during the interview process. The target hiring range for this position is listed below. 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 is committed to the full inclusion of all qualified individuals. As part of this commitment, 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.

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 ML Ops Engineer (Machine Learning Infrastructure) Parallel Systems is seeking an experienced MLOps/ML Infrastructure Engineer to lead the design and development of the scalable systems that power our autonomy and perception pipelines. As we build the first fully autonomous, battery-electric rail vehicles, you will play a critical role in enabling the ML teams to develop, train, and deploy models efficiently and reliably in both R&D and real-world environments. This is an opportunity to take full ownership of the ML infrastructure stack, from distributed training environments and experiment tracking to deployment and monitoring at scale. You'll collaborate closely with world-class engineers in autonomy, robotics, and software, helping shape the core systems that make real-time, safety-critical ML possible. If you're driven by building robust platforms that unlock innovation in AI and robotics, we'd love to work with you. This role requires at least one week a month or more in our LA office per month. Responsibilities: Design and implement robust MLOps solutions, including automated pipelines for data management, model training, deployment and monitoring. Architect, deploy, and manage scalable ML infrastructure for distributed training and inference. Collaborate with ML engineers to gather requirements and develop strategies for data management, model development and deployment. Build and operate cloud-based systems (e.g., AWS, GCP) optimized for ML workloads in R&D, and production environments. Build scalable ML infrastructure to support continuous integration/deployment, experiment management, and governance of models and datasets. Support the automation of model evaluation, selection, and deployment workflows. What Success Looks Like: After 30 Days: You have developed a deep understanding of the product goals, existing infrastructure, and stakeholder requirements. You've conducted technical discovery and proposed a preliminary MLOps architecture-evaluating various ML tools, cloud services, and workflow strategies-clearly outlining pros and cons for each option. After 60 Days: You've delivered a detailed design document that outlines the end-to-end ML pipeline, including data ingestion, model training, deployment, and monitoring. Based on feedback from ML engineers and stakeholders, you've iterated on the design and built PoC for the core ML workflow aligned with the approved architecture. After 90 Days: You have delivered the core features of the MLOps pipeline and successfully integrated key tools (e.g., MLflow, SageMaker, or Kubeflow). You've also initiated the implementation of the remaining features, ensuring the infrastructure supports scalable, repeatable workflows for model experimentation and deployment in both R&D and production environments. Basic Requirements: Bachelor's or higher degree in Computer Science, Machine Learning, or a relevant engineering discipline. 5+ years of experience building large-scale, reliable systems; 2+ years focused on ML infrastructure or MLOps. Proven experience architecting and deploying production-grade ML pipelines and platforms. Strong knowledge of ML lifecycle: data ingestion, model training, evaluation, packaging, and deployment. Hands-on experience with MLOps tools (e.g., MLflow, Kubeflow, SageMaker, Airflow, Metaflow, or similar). Deep understanding of CI/CD practices applied to ML workflows. Proficiency in Python, Git, and system design with solid software engineering fundamentals. Experience with cloud platforms (AWS, GCP, or Azure) and designing ML architectures in those environments. Preferred Qualifications: Experience with deep learning architectures (CNNs, RNNs, Transformers) or computer vision. Hands-on experience with distributed training tools (e.g., PyTorch DDP, Horovod, Ray). Background in real-time ML systems and batch inference, including CPU/GPU-aware orchestration. Previous work in autonomous vehicles, robotics, or other real-time ML-driven systems. We are committed to providing fair and transparent compensation in accordance with applicable laws. Salary ranges are listed below and reflect the expected range for new hires in this role, based on factors such as skills, experience, qualifications, and location. Final compensation may vary and will be determined during the interview process. The target hiring range for this position is listed below. 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 is committed to the full inclusion of all qualified individuals. As part of this commitment, 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.

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 Embedded Software Engineer Parallel Systems is seeking a Senior Embedded Software Engineer to design, develop, and optimize embedded systems that power our autonomous rail vehicles. In this role, you will create robust, real-time software that interfaces directly with hardware components, sensors, and control systems to enable safe and reliable autonomous rail operations. This position requires deep expertise in embedded systems programming, hardware-software integration, and real-time system design, as well as the ability to work closely with hardware engineers and cross-functional teams to deliver production-ready embedded solutions. Responsibilities Design and develop embedded software for bare-metal and RTOS-based systems, ensuring real-time performance and reliability Implement digital communication protocols and interfaces with peripheral devices, sensors, and actuators Architect state machines and command/control systems for autonomous vehicle operations Write high-performance, memory-efficient code primarily in Rust for resource-constrained environments Collaborate with hardware engineers to debug, validate, and optimize hardware-software interfaces Develop comprehensive unit and integration test frameworks for embedded systems using hardware test stands Drive best practices for embedded software development, including code reviews, testing strategies, and documentation What Success Looks Like After 30 Days: You have gained familiarity with our embedded architecture and hardware platforms. You're actively contributing to code reviews and have identified opportunities to improve our testing infrastructure After 60 Days: You've implemented and tested a significant embedded system feature or subsystem, demonstrating proficiency with our development workflow and hardware debugging processes After 90 Days: You've delivered production-ready embedded software that has been validated on target hardware in the field, established new testing patterns that improve system reliability, and are driving technical decisions for upcoming embedded system designs Basic Requirements 5+ years of professional experience in embedded software development Strong proficiency in systems programming languages like C/C++ or Rust. Demonstrated experience with digital communication protocols (SPI, I2C, UART, CAN, etc.) and peripheral device integration on bare metal and RTOS platforms. Expertise in designing and implementing state machines and command/control architectures Hands-on experience with hardware platforms in domains such as autonomous vehicles, aerospace, robotics, or industrial automation Strong commitment to test-driven development with experience building aggressive unit and integration test strategies Solid understanding of real-time constraints, interrupt handling, and resource management in embedded systems Preferred Qualifications Production experience with Rust in embedded environments or strong desire to adopt Rust for systems programming Experience with control systems, PID controllers, or motion control algorithms Electrical engineering skills or formal EE education to facilitate hardware debugging and cross-functional collaboration We are committed to providing fair and transparent compensation in accordance with applicable laws. Salary ranges are listed below and reflect the expected range for new hires in this role, based on factors such as skills, experience, qualifications, and location. Final compensation may vary and will be determined during the interview process. The target hiring range for this position is listed below. Target Salary Range:$150,000-$200,000 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 is committed to the full inclusion of all qualified individuals. As part of this commitment, 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.