LLM Serving Engineer

Qualcomm; San Diego (CA); On-site; USD 123,000 - 184,000; Full time

Benefits offered by this job

Annual bonus

RSU grants

Comprehensive benefits

Job summary

Qualcomm Technologies, Inc. is seeking a Machine Learning Engineer to design and implement ML techniques, frameworks, and tools across product verticals. You will collaborate with cross-functional teams to enhance mobile, edge, auto, and IoT devices through ML hardware and software integration.

The role requires strong background in ML, software, and hardware optimization, with opportunities for impactful innovations and leadership exposure within a large matrixed organization.

Qualifications

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

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.

Skills

Python

C++

Machine Learning

Linux

Education

Bachelor's degree

Master's degree

PhD

Tools

TensorFlow

Caffe

PyTorch

Keras

Job description

Company:

Qualcomm Technologies, Inc.

Job Area:

Engineering Group, Engineering Group > Machine Learning Engineering

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 Machine Learning Engineer, you will create and implement machine learning techniques, frameworks, and tools that enable the efficient discovery and utilization of state-of-the-art machine learning solutions over a broad set of technology verticals or designs. Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning hardware and software.

Minimum Qualifications:

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

Preferred Qualifications:

• Master's degree in Computer Science, Engineering, Information Systems, or related field.
• 2+ years of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras).
• 2+ years of experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi-media).
• 2+ years of experience with one or more programming language suitable for machine learning (e.g., Python, R, C, C++).
• 2+ years of experience using statistics and probability (e.g., conditional probability, Bayes rule).
• 2+ years experience working in a large matrixed organization.
• 1+ year of experience with low level interactions between operating systems (e.g., Linux, Android, QNX) and Hardware.
• 1+ year of work experience in a role requiring interaction with senior leadership (e.g., Director and above).

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.

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 [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).

Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.

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:

$122,800.00 - $184,200.00

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.