Machine Learning Jobs at Qualcomm with Visa Sponsorship
Machine Learning jobs at Qualcomm involve work on on-device AI, neural processing, and model optimization across media and entertainment applications. The company has an established process for sponsoring international talent in this function, supporting multiple visa pathways from OPT through permanent residency.
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Get Access To All JobsCompany:
Qualcomm Technologies, Inc.
Job Area:
Engineering Group, Engineering Group > Modem Technologies Software
General Summary:
The Modem Machine Learning Engineer applies advanced machine learning techniques to next‑generation modem systems, working across data engineering, model development, deployment, and lifecycle management. This role partners closely with modem, systems, and software teams to deliver production‑ready ML solutions. You will place a strong emphasis on modern deep learning architectures, building scalable MLOps frameworks, and ensuring continuous model health monitoring in dynamic production environments.
Key Responsibilities
- Identify, scope, and prioritize high-impact machine learning use cases within modem and wireless systems.
- Design, develop, and train robust ML/DL models tailored for modem applications, leveraging time-series forecasting, sequence modeling, and modern deep learning architectures.
- Build and integrate automated, end-to-end ML pipelines encompassing data ingestion, feature generation, model training, evaluation, and deployment.
- Design and maintain state-of-the-art MLOps infrastructure to enable reproducible experimentation, strict model versioning, automation, and the scalable onboarding of new ML use cases.
- Deploy and heavily optimize ML models for on-device and modem targets, specifically focusing on HW and firmware integrated environments with strict latency, memory, and compute constraints.
- Implement robust model performance monitoring, establishing KPI regression tracking and automated detection for data and concept drift across both cloud and on-target deployments.
- Collaborate closely across systems, test, and platform teams to ensure a seamless production rollout and sustained model performance over time.
- Design and implement ETL, data platform, MLOps, CI/CD, observability, and governance pipelines across on-premises and cloud environments.
- Build and manage ML data platforms utilizing hands-on experience with AWS (S3, Glue, EMR), containers (Docker, Kubernetes), streaming/messaging (Kafka, RabbitMQ), data platforms (Spark, Databricks, Delta Lake/Iceberg/Hudi, SQL, Postgres), and observability stacks (Prometheus/Grafana, Datadog, Splunk).
Minimum Qualifications:
- Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field.
- Bachelor’s degree with at least 1 year of relevant experience or Master’s degree.
- Strong hands-on programming experience in Python and/or C/C++.
- Solid foundations in machine learning algorithms, probability, statistics, and software engineering principles.
Preferred Qualifications
- Hands-on experience with deep learning architectures including CNNs, RNNs, GRUs, LSTMs, Transformers, and related sequence models.
- Proficiency with industry-standard ML frameworks such as PyTorch, TensorFlow, Keras.
- Proven experience building production-grade ML pipelines capable of handling large-scale structured and unstructured datasets.
- Deep experience with MLOps systems, including experiment tracking, model lifecycle management, CI/CD for ML, and cloud/on-device co-development environments.
- Experience implementing data drift, concept drift, and model performance monitoring using well-defined KPIs in a production setting.
- Strong software engineering skills, including object-oriented design, debugging complex integrated systems, and working within real-time execution constraints.
- Exposure to on-device ML deployment, quantization, and neural network optimization tools.
- Familiarity with cloud ML platforms (e.g., AWS SageMaker), containerization (Docker/Kubernetes), and automation/orchestration tools.
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 to 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).
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.
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:
$104,000.00 - $156,000.00
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.
Company:
Qualcomm Technologies, Inc.
Job Area:
Engineering Group, Engineering Group > Modem Technologies Software
General Summary:
The Modem Machine Learning Engineer applies advanced machine learning techniques to next‑generation modem systems, working across data engineering, model development, deployment, and lifecycle management. This role partners closely with modem, systems, and software teams to deliver production‑ready ML solutions. You will place a strong emphasis on modern deep learning architectures, building scalable MLOps frameworks, and ensuring continuous model health monitoring in dynamic production environments.
Key Responsibilities
- Identify, scope, and prioritize high-impact machine learning use cases within modem and wireless systems.
- Design, develop, and train robust ML/DL models tailored for modem applications, leveraging time-series forecasting, sequence modeling, and modern deep learning architectures.
- Build and integrate automated, end-to-end ML pipelines encompassing data ingestion, feature generation, model training, evaluation, and deployment.
- Design and maintain state-of-the-art MLOps infrastructure to enable reproducible experimentation, strict model versioning, automation, and the scalable onboarding of new ML use cases.
- Deploy and heavily optimize ML models for on-device and modem targets, specifically focusing on HW and firmware integrated environments with strict latency, memory, and compute constraints.
- Implement robust model performance monitoring, establishing KPI regression tracking and automated detection for data and concept drift across both cloud and on-target deployments.
- Collaborate closely across systems, test, and platform teams to ensure a seamless production rollout and sustained model performance over time.
- Design and implement ETL, data platform, MLOps, CI/CD, observability, and governance pipelines across on-premises and cloud environments.
- Build and manage ML data platforms utilizing hands-on experience with AWS (S3, Glue, EMR), containers (Docker, Kubernetes), streaming/messaging (Kafka, RabbitMQ), data platforms (Spark, Databricks, Delta Lake/Iceberg/Hudi, SQL, Postgres), and observability stacks (Prometheus/Grafana, Datadog, Splunk).
Minimum Qualifications:
- Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field.
- Bachelor’s degree with at least 1 year of relevant experience or Master’s degree.
- Strong hands-on programming experience in Python and/or C/C++.
- Solid foundations in machine learning algorithms, probability, statistics, and software engineering principles.
Preferred Qualifications
- Hands-on experience with deep learning architectures including CNNs, RNNs, GRUs, LSTMs, Transformers, and related sequence models.
- Proficiency with industry-standard ML frameworks such as PyTorch, TensorFlow, Keras.
- Proven experience building production-grade ML pipelines capable of handling large-scale structured and unstructured datasets.
- Deep experience with MLOps systems, including experiment tracking, model lifecycle management, CI/CD for ML, and cloud/on-device co-development environments.
- Experience implementing data drift, concept drift, and model performance monitoring using well-defined KPIs in a production setting.
- Strong software engineering skills, including object-oriented design, debugging complex integrated systems, and working within real-time execution constraints.
- Exposure to on-device ML deployment, quantization, and neural network optimization tools.
- Familiarity with cloud ML platforms (e.g., AWS SageMaker), containerization (Docker/Kubernetes), and automation/orchestration tools.
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 to 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).
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.
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:
$104,000.00 - $156,000.00
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.
See all Machine Learning Jobs at Qualcomm
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Jobs at Qualcomm.
Get Access To All JobsTips for Finding Machine Learning Jobs at Qualcomm
Align Your Research Background to NPU Work
Qualcomm ML roles frequently center on neural processing unit optimization and on-device inference. Framing your resume around quantization, model compression, or edge deployment signals direct fit for their hardware-software stack.
Time Your OPT Application Before Offer Acceptance
If you're on F-1 status, confirm your OPT start date aligns with Qualcomm's onboarding window before signing an offer. A gap between graduation and work authorization can delay your start date even after an offer is extended.
Clarify Sponsorship Scope During Recruiter Screens
Qualcomm sponsors multiple visa categories including H-1B, TN, and Green Card pathways. Ask the recruiter directly which categories the ML-specific role supports so you're not caught off guard after the offer stage.
Build a Publication Record in Relevant ML Subfields
Qualcomm files LCAs with DOL classifying ML roles under specialty occupation standards. Peer-reviewed work in areas like generative media models or efficient transformers strengthens the degree-to-role nexus USCIS scrutinizes during H-1B adjudication.
Use Migrate Mate to Filter Verified Sponsorship Roles
Not every ML job posting at Qualcomm reflects current sponsorship availability. Use Migrate Mate to browse open Machine Learning roles at Qualcomm that are verified against recent visa filings, saving you time on applications that won't move forward.
Prepare for PERM by Documenting Unique Qualifications Early
If your role leads to an EB-2 or EB-3 Green Card, the PERM process requires your employer to prove no minimally qualified U.S. worker is available. Documenting niche ML skills like on-device AI for media pipelines upfront strengthens that case.
Frequently Asked Questions
Does Qualcomm sponsor H-1B visas for Machine Learning roles?
Yes, Qualcomm sponsors H-1B visas for Machine Learning positions. The company has a consistent track record of filing H-1B petitions for ML and AI roles, and its in-house immigration team handles the process. Sponsorship is typically discussed after an offer is extended, so confirming eligibility during the recruiter screen saves time on both sides.
Which visa types does Qualcomm commonly sponsor for Machine Learning positions?
Qualcomm sponsors a range of visa categories for ML roles, including H-1B, H-1B1 visa for Singaporean and Chilean nationals, TN visa for Canadian and Mexican candidates, F-1 OPT and CPT for students, J-1 visa for exchange visitors, and EB-2 or EB-3 immigrant visas for longer-term permanent residency pathways. The right category depends on your nationality and current immigration status.
How do I apply for Machine Learning jobs at Qualcomm?
Applications go through Qualcomm's careers portal, where ML roles are listed under AI and machine learning or engineering categories. Tailoring your application to highlight on-device AI, model optimization, or neural network deployment experience improves your chances. Migrate Mate also surfaces open Machine Learning roles at Qualcomm filtered by visa sponsorship eligibility, which helps you prioritize where to apply.
What qualifications does Qualcomm expect for Machine Learning roles?
Most ML positions at Qualcomm require a bachelor's degree at minimum, with master's or PhD credentials strongly preferred for research-oriented roles. Hands-on experience with model quantization, efficient inference, PyTorch or TensorFlow, and hardware-aware ML is frequently emphasized. Roles tied to media and entertainment applications may also expect familiarity with generative models, video understanding, or audio processing pipelines.
How do I understand the H-1B sponsorship timeline for a Qualcomm ML role?
The H-1B cap lottery runs once a year, with registrations typically opening in March and approved petitions taking effect October 1. If you receive an offer outside that window, Qualcomm may bridge your status through OPT or CPT until the next cap cycle. Cap-exempt scenarios, such as a prior H-1B approval, can allow faster filing. Confirm your situation with the recruiter early so your start date is planned around USCIS processing timelines.