Machine Learning Engineer Jobs at Qualcomm with Visa Sponsorship
Machine Learning Engineer jobs at Qualcomm involve working on AI inference, on-device learning, and neural network optimization across its chip and platform ecosystem. The company has an established process for sponsoring work visas for this function, making it a realistic target if you need sponsorship.
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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 Engineer Jobs at Qualcomm
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Engineer Jobs at Qualcomm.
Get Access To All JobsTips for Finding Machine Learning Engineer Jobs at Qualcomm
Align your portfolio to on-device AI
Qualcomm's ML hiring centers on edge inference and model compression for Snapdragon platforms. Projects showing quantization, pruning, or TFLite deployment will resonate more than cloud-focused work when you're preparing your portfolio and resume.
Target roles tied to Qualcomm AI Research
Qualcomm AI Research posts roles separately from its core engineering division. Identifying which team is hiring helps you tailor your application and signals to recruiters that you understand how their ML organization is structured.
Confirm H-1B1 eligibility before applying
Qualcomm sponsors H-1B1 visas alongside H-1B. If you hold a Chilean or Singaporean passport, the H-1B1 is cap-exempt and processes faster. Clarify your nationality and preferred visa type early in conversations with the recruiting team.
Track Qualcomm ML openings through Migrate Mate
Sponsorship-confirmed ML Engineer roles at Qualcomm move quickly. Use Migrate Mate to filter live openings by visa type and role so you're applying to verified positions rather than spending time vetting each listing manually.
Request LCA filing details during offer negotiation
Before signing, ask Qualcomm's HR team which DOL wage level they intend to file your Labor Condition Application under. Your offered salary must meet or exceed that prevailing wage, and misalignment at this stage can delay the H-1B petition.
Extend F-1 OPT with a STEM extension early
Machine Learning Engineering qualifies under STEM OPT extension rules, giving you up to 24 additional months of work authorization. File your STEM extension with USCIS before your initial OPT expires so there's no gap while Qualcomm prepares your H-1B petition.
Frequently Asked Questions
Does Qualcomm sponsor H-1B visas for Machine Learning Engineers?
Yes, Qualcomm sponsors H-1B visas for Machine Learning Engineers and has a dedicated immigration team that manages the process. Given H-1B's annual lottery in April, Qualcomm typically submits registrations for eligible candidates in March. If you're already on OPT or another status, discuss timing with the recruiter early so your petition aligns with the lottery cycle.
How do I apply for Machine Learning Engineer jobs at Qualcomm?
Apply directly through Qualcomm's careers portal at qualcomm.com/careers. Filter by job function or team, such as Qualcomm AI Research or Systems Engineering. Tailor your application to emphasize on-device ML experience, since Qualcomm's work centers on Snapdragon and AI accelerator platforms. You can also browse sponsorship-confirmed openings on Migrate Mate before submitting your application.
Which visa types does Qualcomm commonly use for Machine Learning Engineers?
Qualcomm sponsors H-1B, H-1B1 visa, TN visa, F-1 OPT, F-1 CPT, J-1 visa, and employment-based Green Card categories including EB-2 and EB-3 for this role. H-1B is the most common path for candidates from India and other countries. TN visa is available for Canadian and Mexican nationals whose role qualifies under USMCA occupation categories, and H-1B1 visa applies to Singaporean and Chilean passport holders.
What qualifications does Qualcomm expect for Machine Learning Engineer roles?
Qualcomm typically expects a master's or PhD in Computer Science, Electrical Engineering, or a related field for ML Engineer positions, particularly those within AI Research. Hands-on experience with PyTorch or TensorFlow, familiarity with model optimization techniques like quantization and pruning, and exposure to hardware-aware ML development are consistently valued across their postings.
How do I plan my timeline around Qualcomm's H-1B sponsorship process?
USCIS opens H-1B registration each March, with the lottery drawn shortly after. If selected, Qualcomm files your petition by April 1 for an October 1 start date. That means an offer accepted in late 2025 or early 2026 would typically translate to an October 2026 start. If you're on OPT with time remaining, you can begin work before the H-1B takes effect, provided your OPT expiration and cap-gap coverage align.