machine learning R&D engineer

We are seeking a machine learning R&D engineer to help drive the future of AI-accelerated computer vision on the edge. You will be part of a multidisciplinary team responsible for developing new algorithms adapted and optimized for heterogenous, resource constrained SoC platforms serving mobile, automotive, XR, IOT, and robotics customers. This role is ideal for someone who thrives at the intersection of cutting-edge computer vision algorithms, AI models, and efficient hardware/software implementation applied to real-world problems. You will have the opportunity to propose new IP, contribute to industry conferences, influence system-level architecture, and be part of a world-class team that drives solutions from research through production deployment.

Principal Duties and Responsibilities

• Leverage advanced video and computer vision engineering expertise to research, design, and implement critical video processing and computer vision algorithms, including depth estimation, sparse and dense optical flow, video super-resolution and denoising, 3D reconstruction, visual odometry and SLAM.
• Develop optimized model architectures and training strategies for deployment of deep learning at the edge, incorporating the latest advances from literature such as transformers, attention, VLA/VLM, and world models.
• Profile and optimize algorithm and model performance across memory, compute, power, and bandwidth constraints on mobile and embedded platforms.
• Collaborate closely with cross-functional teams (hardware, software, systems, and product) to ensure new algorithms meet customer requirements. Develop meaningful supervised and non-reference quality metrics to assess model performance for different use cases.
• Own the training and development of new release models for important customer segments.
• Write clear and concise technical documentation, design specifications, and feature descriptions to guide internal teams and external partners.
• Contribute effectively in a fast-paced, highly collaborative environment with globally distributed, cross-functional teams., Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail or call Qualcomm’s toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).

Bachelor’s degree in Computer or Electrical Engineering, Computer Science, or related field and 2+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience. OR Master’s degree in Computer or Electrical Engineering, Computer Science, or related field and 1+ year of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience. OR PhD in Computer or Electrical Engineering, Computer Science, or related field.

Preferred Qualifications

• Strong background in computer vision and video processing algorithms. 3+ years of experience developing and implementing computer vision and video algorithms within system-level products.
• Hands-on experience with modern deep learning architectures.
• Strong coding skills in Python (C/C++ is a plus) for production-quality development, optimization, and on-device deployment, with experience using ML/CV frameworks such as PyTorch, TensorFlow, ONNX, and OpenCV.
• Comfortable using the latest AI coding assistants and productivity tools to aid development and perform critical analysis (Claude Code, Cursor, ChatGPT, etc.). Understands the tradeoffs of using AI and values code quality.
• Strong ability to work across algorithm, software, and hardware boundaries.
• Experience deploying AI algorithms on the edge (ExecuTorch, Jetpack, QNN, etc.) and understanding of associated tradeoffs and resource limitations (power, memory bandwidth, etc.)
• 3+ years of experience working in a large, matrixed organization.
• Publication, patent, or external technical contribution experience is a plus.

Level of Responsibility

• Self starter, works independently with minimal supervision.

• Decision-making impacts work beyond the immediate work group.

• Requires strong verbal and written communication skills. Comfortable in a research and development environment, proposing and defending new ideas, and presenting results to internal groups.
• Owns the development and release process for a major algorithm feature, working with stakeholders to ensure requirements are met.
• Tasks require multi-step planning, prioritization, and problem-solving, with flexibility in execution order to achieve objectives efficiently.

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

Pay range and Other Compensation & Benefits: $129,500.00 - $194,300.00

The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer - and you can review more details about our US benefits at this link.