AI ML Engineer Jobs at Qualcomm with Visa Sponsorship
Qualcomm hires AI ML Engineers to build the machine learning systems behind its chip platforms, on-device AI, and media processing pipelines. The company has a structured immigration program that supports international candidates across multiple visa categories, making it a realistic target for sponsored roles.
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INTRODUCTION
We are looking for an experienced Windows platform architect to drive AI system performance and power enhancements into the SW and HW stacks and SW tools of state-of-the-art machine learning solutions on Snapdragon platform such that the AI performance and power is delivered to final applications while keeping application developer experience and ease of deployment competitively high. As a senior member of the team responsible for competitive advantages in end-to-end delivery of AI functionality, performance, power on Snapdragon compute platform, you will have opportunity to drive joint HW-SW design and architecture spec while representing requirements of Windows on Snapdragon application developers for multiple AI use-cases and ensure the Snapdragon AI platform, and tools deliver the industry leading performance and power including necessary security requirements. You will also study Enterprise agentic AI workflows, define, and drive implementation of on-device AI platform components such that Snapdragon becomes the preferred choice for Enterprise AI PCs. You will work closely with software and hardware architects, project engineers, product managers, customer engineers, OEMs, OS partners and application developers. Ideal candidate has extensive experience in architecture aware AI Model system performance optimization on Windows PC/Laptop, architecture aware benchmarking, and performance breakdown analysis with GPU, NPU, and knowledge of state of the art in AI for multiple domains such as Computer Vision, Audio, Generative AI, Agentic AI.
ROLE AND RESPONSIBILITIES
Understand trends in ML network design, through customer engagements and latest state of the art, and determine how this will affect both SW and HW design
Analyze bottlenecks in end to end use-cases and application of ML/AI algorithms and workloads on exploratory and existing Qualcomm HW and SW stacks through simulation and on-device characterization
On-device correlation and tuning of algorithm versus pre-silicon predictions
Analyze Enterprise AI workflows for common user personas and propose components that make Snapdragon AI PCs work complimentarily with cloud AI components of the enterprise workflow to deliver measurably increased productivity and user-experience for enterprise users
Interface with other cross-site and cross-functional teams to arrive at best-in-class performant reference implementations, tools, and documentation that are directly leveraged by 3rd party app developers
Analyze, develop, propose new features and designs to system design of next gen SoCs that reduce performance bottlenecks through the workflow
MINIMUM QUALIFICATIONS
* Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 8+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 7+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
SKILLS AND EXPERIENCE
Excellent understanding of AI frameworks (e.g., TensorFlow, PyTorch), GPU/NPU programming, and parallel computing. Experience with large language models/foundational models development and deployment a plus
Good Understanding of complete Software stack and familiarity with AI and other multimedia hardware acceleration technologies
Experience with performance optimization of AI application on Windows using processor specific optimization tools/libraries/primitives on GPU, NPU
Strong background in end to end system performance analysis using profiling tools, and algorithmic modification methods for performance improvement is essential
Knowledge of state of the art in Agentic AI
Knowledge of computer architecture, embedded system implementations
Strong software engineering principles are essential
Proficiency in programming languages such as Python, C++
Excellent communication skills to articulate complex technical concepts to non-technical and technical stakeholders
Strong leadership abilities to motivate and guide development teams
Detail-oriented with strong problem-solving, analytical, and debugging skills with the ability to think strategically and drive innovative solutions
Demonstrated ability to learn, think and adapt in a fast-changing environment
Familiarity with software development methodologies, version control systems, and agile project management practices
15+ years experience in High Performance Computing System Engineering or Software with 5+ years in AI system optimization
* Masters or PhD in Computer Science or Electrical Engineering
EEO Employer: 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
$200,800.00 - $301,200.00
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. If you would like more information about this role, please contact Qualcomm Careers.
To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.

INTRODUCTION
We are looking for an experienced Windows platform architect to drive AI system performance and power enhancements into the SW and HW stacks and SW tools of state-of-the-art machine learning solutions on Snapdragon platform such that the AI performance and power is delivered to final applications while keeping application developer experience and ease of deployment competitively high. As a senior member of the team responsible for competitive advantages in end-to-end delivery of AI functionality, performance, power on Snapdragon compute platform, you will have opportunity to drive joint HW-SW design and architecture spec while representing requirements of Windows on Snapdragon application developers for multiple AI use-cases and ensure the Snapdragon AI platform, and tools deliver the industry leading performance and power including necessary security requirements. You will also study Enterprise agentic AI workflows, define, and drive implementation of on-device AI platform components such that Snapdragon becomes the preferred choice for Enterprise AI PCs. You will work closely with software and hardware architects, project engineers, product managers, customer engineers, OEMs, OS partners and application developers. Ideal candidate has extensive experience in architecture aware AI Model system performance optimization on Windows PC/Laptop, architecture aware benchmarking, and performance breakdown analysis with GPU, NPU, and knowledge of state of the art in AI for multiple domains such as Computer Vision, Audio, Generative AI, Agentic AI.
ROLE AND RESPONSIBILITIES
Understand trends in ML network design, through customer engagements and latest state of the art, and determine how this will affect both SW and HW design
Analyze bottlenecks in end to end use-cases and application of ML/AI algorithms and workloads on exploratory and existing Qualcomm HW and SW stacks through simulation and on-device characterization
On-device correlation and tuning of algorithm versus pre-silicon predictions
Analyze Enterprise AI workflows for common user personas and propose components that make Snapdragon AI PCs work complimentarily with cloud AI components of the enterprise workflow to deliver measurably increased productivity and user-experience for enterprise users
Interface with other cross-site and cross-functional teams to arrive at best-in-class performant reference implementations, tools, and documentation that are directly leveraged by 3rd party app developers
Analyze, develop, propose new features and designs to system design of next gen SoCs that reduce performance bottlenecks through the workflow
MINIMUM QUALIFICATIONS
* Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 8+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 7+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
SKILLS AND EXPERIENCE
Excellent understanding of AI frameworks (e.g., TensorFlow, PyTorch), GPU/NPU programming, and parallel computing. Experience with large language models/foundational models development and deployment a plus
Good Understanding of complete Software stack and familiarity with AI and other multimedia hardware acceleration technologies
Experience with performance optimization of AI application on Windows using processor specific optimization tools/libraries/primitives on GPU, NPU
Strong background in end to end system performance analysis using profiling tools, and algorithmic modification methods for performance improvement is essential
Knowledge of state of the art in Agentic AI
Knowledge of computer architecture, embedded system implementations
Strong software engineering principles are essential
Proficiency in programming languages such as Python, C++
Excellent communication skills to articulate complex technical concepts to non-technical and technical stakeholders
Strong leadership abilities to motivate and guide development teams
Detail-oriented with strong problem-solving, analytical, and debugging skills with the ability to think strategically and drive innovative solutions
Demonstrated ability to learn, think and adapt in a fast-changing environment
Familiarity with software development methodologies, version control systems, and agile project management practices
15+ years experience in High Performance Computing System Engineering or Software with 5+ years in AI system optimization
* Masters or PhD in Computer Science or Electrical Engineering
EEO Employer: 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
$200,800.00 - $301,200.00
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. If you would like more information about this role, please contact Qualcomm Careers.
To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
See all 45+ AI ML Engineer at Qualcomm jobs
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Get Access To All JobsTips for Finding AI ML Engineer Jobs at Qualcomm Jobs
Align your portfolio to on-device AI
Qualcomm's AI ML hiring centers on inference optimization, neural network quantization, and edge deployment. Preparing project work or publications that demonstrate these skills specifically positions you ahead of candidates with only cloud-side ML backgrounds.
Target teams working on Hexagon DSP
Qualcomm's AI Engine and Hexagon processor teams post ML roles that blend hardware-aware model development with software. Identifying job postings that reference these platforms tells you which hiring managers are most likely running active sponsorship pipelines.
Confirm LCA filing before accepting an offer
Your employer must file a certified Labor Condition Application with DOL before submitting your H-1B petition to USCIS. Ask your Qualcomm recruiter for a timeline on LCA certification so you can plan your start date without assuming immediate work authorization.
Use OPT strategically during the H-1B gap
If you're on F-1 OPT and miss the H-1B lottery, a STEM OPT extension gives you up to 24 additional months. Qualcomm is an E-Verify participant, which is a mandatory requirement for STEM OPT extensions, so your authorization won't be interrupted while you wait for the next cap season.
Understand Qualcomm's PERM pathway for senior roles
For senior or staff-level AI ML positions, Qualcomm often initiates PERM-based Green Card sponsorship. DOL's PERM process typically takes 12 to 18 months before an I-140 petition can be filed, so raise long-term sponsorship intent early in final-round interviews.
Browse open roles before your job search stalls
Filter for AI ML Engineer openings at Qualcomm that explicitly support visa sponsorship using Migrate Mate. Seeing which specific teams are actively hiring helps you tailor your outreach rather than applying broadly across a company of this size.
AI ML Engineer at Qualcomm jobs are hiring across the US. Find yours.
Find AI ML Engineer at Qualcomm JobsFrequently Asked Questions
Does Qualcomm sponsor H-1B visas for AI ML Engineers?
Yes. Qualcomm sponsors H-1B visas for AI ML Engineers and has a well-established immigration support program for technical roles. Because Qualcomm participates in the H-1B cap each year, sponsorship is subject to the annual lottery. If you're already on an approved H-1B with another employer, a transfer to Qualcomm avoids the lottery entirely.
How do I apply for AI ML Engineer jobs at Qualcomm?
Apply directly through Qualcomm's careers portal, targeting roles that list your specific ML discipline, whether that's model training, inference optimization, or on-device deployment. Tailor your resume to Qualcomm's focus areas, such as its AI Engine and Snapdragon platforms. You can also browse verified sponsorship-eligible openings at Qualcomm through Migrate Mate before applying.
Which visa types does Qualcomm commonly use for AI ML Engineer roles?
Qualcomm sponsors H-1B, H-1B1, TN, J-1, and F-1 OPT and CPT for AI ML Engineer positions, alongside EB-2 and EB-3 Green Card pathways for longer-term sponsorship. H-1B is the most common route for full-time hires. TN is available to Canadian and Mexican nationals in qualifying ML roles. H-1B1 is a cap-exempt option for Chilean and Singaporean nationals.
What qualifications does Qualcomm expect for AI ML Engineer positions?
Most AI ML Engineer roles at Qualcomm require a Master's or PhD in computer science, electrical engineering, or a closely related field, given the hardware-adjacent nature of the work. Practical experience with deep learning frameworks, model compression, and deployment on resource-constrained devices is weighted heavily. Publications or prior work with quantization, pruning, or neural architecture search are strong differentiators in technical screenings.
How long does the H-1B sponsorship process take at a company like Qualcomm?
For cap-subject H-1B petitions, the timeline is tied to USCIS's annual lottery, which opens in March for an October 1 start date. After selection, standard processing runs three to five months. Qualcomm typically uses premium processing for critical hires, which reduces USCIS adjudication to 15 business days. Factor in DOL's LCA certification, which precedes the petition and usually takes seven to ten business days.
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