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Work From Home Qualcomm Machine Learning Jobs (NOW HIRING)

As a Qualcomm Machine Learning Engineer, you will create and implement machine learning techniques ... at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to ...

From Home / Beach / Mountain / Cafe / Anywhere! * We are a remote-first company with a globally distributed team. You can find your productive zone and work from there. About The Role As a Machine ...

Role We are looking for a Staff Machine Learning Engineer to help us build a best in class ML ... Remote-First Team - Work from anywhere in the U.S. * Unlimited PTO & 10 Holidays - So you can relax ...

Role We are looking for a Senior Machine Learning Engineer to help us build a best in class ML ... Remote-First Team - Work from anywhere in the U.S. * Unlimited PTO & 10 Holidays - So you can relax ...

Senior Machine Learning Engineer

$125K - $165K/yr

This is a fully remote position, allowing you to work from home or location of record within the U ... Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning ...

Senior Machine Learning Engineer

$125K - $165K/yr

This is a fully remote position, allowing you to work from home or location of record within the U ... Our machine learning engineering team is responsible for developing infrastructure and tooling to ...

Senior Machine Learning Engineer

Chicago, IL · On-site +1

$150K - $185K/yr

POSITION SUMMARY The Senior Machine Learning Engineer is responsible for designing, building, and ... Our remote friendly culture offers flexibility and the comfort of working from home, while also ...

As a Senior Machine Learning Engineer, you will own the end to end ML lifecycle at Button, from the ... Button provides employees with a RemotePlus workplace, which blends "work from anywhere" with in ...

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Work From Home Qualcomm Machine Learning information

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$13

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$32

How much do work from home qualcomm machine learning jobs pay per hour?

As of Jun 5, 2026, the average hourly pay for work from home qualcomm machine learning in the United States is $21.84, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $26.44 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Work From Home Qualcomm Machine Learning Engineer, and why are they important?

To excel as a Work From Home Qualcomm Machine Learning Engineer, a strong background in computer science, statistics, and machine learning algorithms is essential, often supported by a relevant degree. Familiarity with programming languages such as Python or C++, experience with machine learning frameworks like TensorFlow or PyTorch, and knowledge of Qualcomm's hardware platforms are typically required. Excellent problem-solving abilities, self-motivation, and strong communication skills help individuals collaborate remotely and contribute effectively to team goals. These skills ensure the successful development and deployment of optimized machine learning solutions tailored for Qualcomm's innovative technologies.

How does a remote Qualcomm Machine Learning engineer typically collaborate with on-site teams and contribute to large-scale projects?

As a remote Qualcomm Machine Learning engineer, you'll regularly interact with cross-functional teams through virtual meetings, code reviews, and collaboration tools such as Slack and Jira. You'll contribute to large-scale projects by developing, testing, and optimizing ML models, often working with both hardware and software colleagues. Clear communication and proactive documentation are essential, as you'll need to sync project goals and updates across time zones. You'll also participate in virtual brainstorming sessions and technical discussions, ensuring your contributions seamlessly integrate with the broader team's efforts.

What are 'Work From Home Qualcomm Machine Learning' jobs?

Work From Home Qualcomm Machine Learning jobs are remote positions offered by Qualcomm that focus on developing, testing, and implementing machine learning algorithms and models. Employees in these roles use their expertise in artificial intelligence, data science, and software engineering to create innovative solutions for Qualcomm’s products and services, such as mobile devices and wireless technology. Working from home allows professionals to perform these tasks remotely, collaborating with team members through digital communication tools. These positions typically require a background in computer science, machine learning, or related fields, and often involve programming, data analysis, and research.

What is the difference between Work From Home Qualcomm Machine Learning vs Work From Home Qualcomm Data Scientist?

AspectQualcomm Machine Learning EngineerQualcomm Data Scientist
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML frameworksBachelor's/Master's in CS, Statistics, or related; experience in data analysis
Work EnvironmentRemote, collaborative teams focused on ML model developmentRemote, analyzing large datasets to inform business decisions
Industry UsageDeveloping ML algorithms for hardware and software productsInterpreting data to optimize products and strategies

Work From Home Qualcomm Machine Learning engineers focus on developing and implementing machine learning models, while Qualcomm Data Scientists analyze data to support decision-making. Both roles often work remotely, require similar technical backgrounds, but differ in their core responsibilities and application areas.

More about Work From Home Qualcomm Machine Learning jobs
What cities are hiring for Work From Home Qualcomm Machine Learning jobs? Cities with the most Work From Home Qualcomm Machine Learning job openings:
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What job categories do people searching Work From Home Qualcomm Machine Learning jobs look for? The top searched job categories for Work From Home Qualcomm Machine Learning jobs are:
Staff Software Engineer

Staff Software Engineer

Qualcomm

Santa Clara, CA • On-site, Remote

Full-time

Posted 14 days ago


Qualcomm rating

9.6

Company rating: 9.6 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

4th of 186 rated software companies


Job description

Company:
Qualcomm Technologies, Inc.
Job Area:
Engineering Group, Engineering Group > Machine Learning Engineering
General Summary:
As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Machine Learning Engineer, you will create and implement machine learning techniques, frameworks, and tools that enable the efficient discovery and utilization of state-of-the-art machine learning solutions over a broad set of technology verticals or designs. Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning hardware and software.
Minimum Qualifications:
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ 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 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
Preferred Qualifications:
• Master's degree or PhD in Computer Science, Electrical/Computer Engineering, Robotics, or a related field with specialization in edge AI, computer vision, or embedded ML.
• 5+ years of experience with performance-critical programming in C++, Python, including hardware-aware optimization.
• 5+ years of experience with modern ML framework such as PyTorch, ONNX Runtime, TensorRT, TVM, OpenVINO, or Qualcomm's AI toolchain including SNPE, QNN.
• 3+ years of experience developing real-time edge AI systems with emphasis on vision, multimodal perception, and sensor fusion.
• Strong background in applied statistics, probabilistic modeling, and evaluation of ML systems under real-world constraints such as latency, thermal limits, and bandwidth.
• Familiar with FFmpeg, GStreamer with solid knowledge of video codec and streaming technologies.
• Experience with computer vision and intelligent video analytics, including object detection, tracking, re-identification, camera geometry and calibration, and cross-camera association.
• Experience working in large cross-functional organizations involving hardware, firmware, cloud, and product teams.
• Experience leading technical initiatives, mentoring engineers, or driving architectural decisions.
• Experience presenting technical strategy or results to senior leadership.
Principal Duties and Responsibilities:
• Lead the design, development, and optimization of edge AI systems for real-time video analytics, spanning model architectures, inference pipelines, and runtime frameworks deployed on AI camera and embedded platforms.
• Develop and integrate advanced computer vision and video analytics algorithms to deliver robust, production-grade AI cameras and edge computer vision solutions.
• Design and optimize real-time video processing pipelines, leveraging FFmpeg, GStreamer, and streaming protocols to handle high-throughput, low-latency video ingestion, preprocessing, inference, and post-processing.
• Apply and evaluate machine learning techniques under real-world constraints, incorporating system-level considerations such as bandwidth, compute budget, memory footprint, thermal limits, and end-to-end latency.
• Prototype, validate, and productionize novel ML solutions aligned with product roadmaps, transforming research concepts into reliable customer-facing features.
• Lead experimental design, model training, benchmarking, and validation, establishing metrics, evaluation frameworks, and best practices to ensure model accuracy, robustness, and system performance at scale.
• Provide technical leadership across the organization, mentoring engineers, reviewing designs, and driving architectural decisions that shape the long-term evolution of the ML and edge AI platform.
• Communicate technical strategy, trade-offs, and results effectively to cross-functional stakeholders and senior leadership, influencing product direction and execution.
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).
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:
$160,500.00 - $240,700.00
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.

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About Qualcomm

Sourced by ZipRecruiter

Qualcomm is enabling a world where everyone and everything can be intelligently connected. You interact with products and technologies made possible by Qualcomm every day, including 5G-enabled smartphones that double as pro-level cameras and gaming devices, smarter vehicles and cities, and the technology behind the smart, connected factories that manufactured your latest purchase. Our powerful connectivity solutions keep you connected—even in remote areas. Qualcomm 5G and AI innovations are the power behind the connected intelligent edge. You’ll find our technologies behind and inside the innovations that deliver significant value across multiple industries and to billions of people every day.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Diego, CA, US

Year founded

1985