ML Engineer Jobs at Qualcomm with Visa Sponsorship
ML Engineer jobs at Qualcomm sit at the intersection of hardware-aware inference, on-device AI, and signal processing, shaped by the company's deep semiconductor roots. Qualcomm has a well-established sponsorship practice across multiple visa categories, making it a realistic target for international engineers pursuing U.S. work authorization.
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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 ML Engineer Jobs at Qualcomm
Sign up for free to unlock all listings, filter by visa type, and get alerts for new ML Engineer Jobs at Qualcomm.
Get Access To All JobsTips for Finding ML Engineer Jobs at Qualcomm
Align your portfolio to on-device AI
Qualcomm's ML hiring centers on model quantization, edge inference, and hardware-software co-design for platforms like Snapdragon. Projects demonstrating deployment on resource-constrained hardware carry more weight than cloud-centric deep learning work.
Distinguish your visa category early
Qualcomm sponsors multiple visa types, so confirm whether your situation fits H-1B, H-1B1 visa, TN, or F-1 OPT before your first recruiter call. Walking in with that clarity prevents misaligned expectations during offer negotiation.
Time OPT applications around Qualcomm's recruiting cycle
If you're on F-1 OPT, submit your EAD application to USCIS at least 90 days before your program end date. Qualcomm's campus and new-grad hiring peaks in fall, so your work authorization timeline needs to align with that window.
Prepare a specialty occupation paper trail
For H-1B sponsorship, Qualcomm's legal team will build a specialty occupation case around your role. Pull your official transcripts, any published research, and project documentation in advance so nothing slows the I-129 filing once an offer is extended.
Search verified sponsorship listings through Migrate Mate
Filter for ML Engineer openings at Qualcomm using Migrate Mate, which surfaces roles by visa type so you can target positions that match your specific authorization pathway rather than sorting through general job boards.
Account for PERM if you want a Green Card path
Qualcomm sponsors EB-2 and EB-3 Green Cards, which require DOL PERM labor certification before an I-140 petition can be filed. That process typically takes one to two years before priority date movement even begins, so factor that timeline into any long-term plans.
Frequently Asked Questions
Does Qualcomm sponsor H-1B visas for ML Engineers?
Yes, Qualcomm sponsors H-1B visas for ML Engineer roles and has a dedicated immigration support function that works with outside counsel on I-129 petitions. Because H-1B is subject to the annual lottery, your offer timing relative to the April registration window matters. Qualcomm also sponsors H-1B1 visa for eligible nationals, which is not lottery-dependent and can be a faster path.
How do I apply for ML Engineer jobs at Qualcomm?
Applications go through Qualcomm's careers portal, where ML Engineer roles are listed under engineering and artificial intelligence categories. For a filtered view showing only visa-sponsoring positions, use Migrate Mate to browse current Qualcomm openings by visa type. Tailoring your resume to reflect on-device inference, Snapdragon platform experience, or model optimization will strengthen your application for these roles specifically.
Which visa types does Qualcomm commonly use for ML Engineer roles?
Qualcomm uses H-1B and H-1B1 visa most frequently for ML Engineers already outside the U.S. or transitioning from other status. F-1 OPT and CPT cover students and recent graduates, and TN visa is available for qualified Canadian and Mexican nationals in eligible classification categories. For longer-term pathways, Qualcomm supports EB-2 and EB-3 Green Card sponsorship, including PERM labor certification through the DOL.
What qualifications does Qualcomm expect for ML Engineer candidates?
Most ML Engineer roles at Qualcomm require a master's or Ph.D. in computer science, electrical engineering, or a closely related field, with specialization in machine learning or deep learning. Practical experience with model compression, quantization-aware training, or neural architecture search is frequently emphasized in job descriptions. Familiarity with Qualcomm's AI stack or prior work on embedded or mobile inference platforms strengthens a candidate's profile considerably.
How do I navigate the visa sponsorship process timeline at Qualcomm?
If you're offered an H-1B, Qualcomm's legal team initiates the USCIS filing process, but you should clarify your start date against the October 1 cap-subject employment start constraint. For F-1 OPT extensions via STEM OPT, USCIS recommends filing at least 90 days before OPT expiration. J-1 visa holders should verify whether their program carries a two-year home residency requirement before accepting an H-1B offer, since that restriction requires a waiver before status change.