Jobs
Company:
Qualcomm India Private Limited:
Job Area:
Engineering Group, Engineering Group > Systems Engineering
General Summary:
We are seeking a highly skilled engineer to enable highly optimized mapping of AI workloads to Qualcomm’s next generation system-technology solutions for the slowing Moore’s law era. The focus is on identifying the system and technology bottlenecks for the state-of-the-art and emerging AI workloads e.g. the mixture-of-experts (MoE), multi-tenant vector databases, multimodal physical AI etc.. The E2E system KPIs for mapping these emerging AI workloads include the power, performance and TCO of the entire system encompassing the SoC, memory and networking.
The primary role of the candidate is to map the workloads using both internal and external tools to Qualcomm’s next-gen AI accelerator systems and carry out what-if scenarios of optimizing different underlying components e.g. SoC, memory, networking and other technology features for the best power-performance-TCO trade-off. The candidate also needs to ensure which AI workloads are relevant for the different business units (BUs) from datacenters to physical AI to computing devices.
To drive these technologies the person will collaborate with high-level representatives across functional teams (e.g. Architecture, product management, SW teams) to enable an implementation strategy that meets system requirements.
Minimum Qualifications:
- Bachelor's degree in Science, Engineering, or related field and 6+ years of ASIC design, verification, validation, integration, or related work experience.OR
Master's degree in Science, Engineering, or related field and 5+ years of ASIC design, verification, validation, integration, or related work experience.
OR
PhD in Science, Engineering, or related field and 4+ years of ASIC design, verification, validation, integration, or related work experience.
Preferred Qualifications:
· Thorough understanding of E2E system KPI dependency e.g. power, performance and TCO of emerging AI workloads mixture-of-experts (MoE), multi-tenant vector databases, multimodal physical AI.
· Ability to quickly map newer workloads onto Qualcomm systems using internal and external tools so high proficiency in scripting (python or similar) is required.
· Great knowledge of state-of-art workloads across multiple BUs.
· Master's or Ph.D. in Electrical Engineering, Computer Science, or a related field
· Exceptional creativity to innovate new ideas and develop innovative products/ processes without established objectives or known parameters.
· Verbal and written communication skills to convey highly complex and/or detailed information. Will require strong negotiation and influence with large groups or high-level constituents
· Ability to work independently and as part of a team
· Most tasks do not have defined steps; simultaneous use of multiple mental abilities is generally required to determine the best approach
· Deductive and inductive problem solving is required; multiple approaches may be taken/necessary to solve the problem; often information is missing or conflicting; advanced data analysis and interpretation skills are required.
Keywords: LLM, Computer Architecture, Performance Analysis
Minimum Qualifications:
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience. OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
Applicants: 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 disability-accomodations@qualcomm.com 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 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.
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.
If you would like more information about this role, please contact Qualcomm Careers.
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About Qualcomm

Qualcomm
PublicInventing the technologies the world loves.
10,001+
Employees
San Diego
Headquarters
Reviews
3.6
5 reviews
Work Life Balance
4.0
Compensation
4.0
Culture
2.5
Career
3.0
Management
2.5
Pros
Good work-life balance
Real engineering work with technical challenges
Good compensation
Cons
Slow processes and bureaucracy
Poor management and planning
Cross-team dependencies and alignment issues
Salary Ranges
1 data points
Junior/L3
Junior/L3 · Data Scientist
0 reports
$215,000
total / year
Base
$170,000
Stock
$30,000
Bonus
$15,000
$182,750
$247,250
Interview Experience
8 interviews
Difficulty
3.4
/ 5
Duration
14-28 weeks
Experience
Positive 0%
Neutral 50%
Negative 50%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Technical Interview/Onsite
5
Team Matching
6
Offer
Common Questions
Coding/Algorithm
Technical Knowledge
System Design
Behavioral/STAR
Past Experience
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