Engineer, Senior Staff-AI Systems Engineer (Auto/Robotics)

Job Posting Date

2025-09-16

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General Summary:

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Systems Engineer, you will research, design, develop, simulate, and/or validate systems-level software, hardware, architecture, algorithms, and solutions that enables the development of cutting-edge technology. Qualcomm Systems Engineers collaborate across functional teams to meet and exceed system-level requirements and standards.

Minimum Qualifications:

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience.

OR

Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Systems Engineering or related work experience.

OR

PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.

We are seeking experts with a robust background in the field of deep learning (DL) to design state-of-the-art low-level perception (LLP), end-to-end models and Vision-Language models(VLM)/ Vision-Language-Action models(VLA) for Autonomous Driving and Robotics use cases, with a focus on achieving accuracy-latency Pareto optimality. This role involves comprehending state-of-the-art research in this field and deploying networks on the Qualcomm Ride platform Autonomous driving and Robotics applications.

The ideal candidate must be well-versed in recent advancements in Vision Transformers (Cross-attention, Self-attention), lifting 2D features to Bird's Eye View (BEV) space, their applications to multi-modal fusion and VLM/VLA Models. This position offers extensive opportunities to collaborate with advanced R&D teams of leading automotive Original Equipment Manufacturers (OEMs) as well as Qualcomm's internal stack teams. The team is responsible for enhancing the speed, accuracy, power consumption, and latency of deep networks running on Snapdragon Ride AI accelerators.

A thorough understanding of machine learning algorithms, particularly those related to Automotive and Robotics use cases is essential. Research experience in the development of efficient networks, various Neural Architecture Search (NAS) techniques, network quantization, and pruning is highly desirable.

Strong communication and interpersonal skills are required, and the candidate must be able to work effectively with various horizontal AI teams.

Preferred Qualifications:

• Candidates with a broad spectrum of experience, 12+ years in the relevant domain.
• Good at software development with excellent analytical, development, and problem-solving skills.
• Strong understanding of Machine Learning fundamentals
• Hands-on experience with deep learning network design and implementation. Ability to define network from scratch in PyTorch, ability to add new loss function, modify network with torch.fx. Adept at version control system like GIT.
• Experience in neural network quantization, compression, pruning algorithms.
• Experience in deep learning kernel/compiler optimization
• Strong communication skills

Principal Duties and Responsibilities:

• Applies Machine Learning knowledge to extend training or runtime frameworks or model efficiency software tools with new features and optimizations.

• Models, architects, and develops machine learning hardware (co-designed with machine learning software) for inference or training solutions.

• Develops optimized software to enable AI models deployed on hardware (e.g., machine learning kernels, compiler tools, or model efficiency tools, etc.) to allow specific hardware features; collaborates with team members for joint design and development.

• Assists with the development and application of machine learning techniques into products and/or AI solutions to enable customers to do the same.

• Develops, adapts, or prototypes complex machine learning algorithms, models, or frameworks aligned with and motivated by product proposals or roadmaps with minimal guidance from more experienced engineers.

• Conducts complex experiments to train and evaluate machine learning models and/or software independently.

Level of Responsibility:

• Works independently with minimal supervision.

• Decision-making may affect work beyond immediate work group.

• Requires verbal and written communication skills to convey information. May require basic negotiation, influence, tact, etc.

• Has a moderate amount of influence over key organizational decisions (e.g., is consulted by senior leadership to make key decisions).

• Tasks require multiple steps which can be performed in various orders; some planning, problem-solving, and prioritization must occur to complete the tasks effectively.