Deep Learning Researcher Jobs
Deep Learning Researcher jobs are open from new-grad to principal and staff levels across technology, healthcare, autonomous systems, and defense, with specializations in computer vision, natural language processing, and generative model development. See the openings below and apply to the ones that match your experience.
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Showing 5 of 56+ Deep Learning Researcher jobs
Company:
Qualcomm Technologies, Inc.Job Area:
Engineering Group, Engineering Group > Machine Learning ResearcherGeneral Summary:
Qualcomm AI Research is seeking world-class researchers to help push the boundaries of artificial intelligence and machine learning. Our team pioneers new algorithms, models, and systems that advance the state of the art while delivering exceptional performance with unprecedented power, memory, and computational efficiency.
Our multidisciplinary team brings together expertise across algorithms, software, hardware, and systems. We pursue fundamental and applied research, from foundational theories and novel learning algorithms to efficient AI systems deployed on resource-constrained devices. Working closely with Qualcomm's business and engineering teams, we translate research breakthroughs into technologies deployed worldwide across mobile, compute, automotive, robotics, cloud, XR, and IoT platforms, while publishing at leading AI conferences.
Our team has demonstrated world-first research breakthroughs and proof-of-concepts across model efficiency, representation learning, perception and understanding, generative and foundation models, reasoning and agentic intelligence, and embodied and physical AI. Our research contributions have earned numerous best paper awards, major research competition wins, and top rankings on AI and computer vision benchmarks. We also translate these breakthroughs into highly optimized AI models, end-to-end workflows, and developer tools for Qualcomm platforms, making many innovations accessible to all. Explore our research and innovations:
- Research Breakthroughs and Demonstrations
- Qualcomm AI Research Publications and Innovations Qualcomm AI Hub: Optimized Models and Workflows
Role Responsibilities:
Research interns will contribute to fundamental and applied research in artificial intelligence and machine learning, developing novel algorithms, models, and systems that advance the state of the art. Research opportunities span a broad range of areas, including:
- Generative AI and Foundation Models: Large language models (LLMs), multimodal foundation models, vision-language models (VLMs), vision-language-action models (VLAs), world models, and generative modeling for language, image, video, audio, and 3D content. Research topics include diffusion and autoregressive models, mixture-of-experts, parallel decoding, long-context modeling, and knowledge distillation.
- Agentic AI and Reasoning: Autonomous agents, multi-agent systems, reasoning, planning, and verification; memory management, retrieval-augmented generation (RAG), inference-time optimization, robustness, alignment, AI safety, and hallucination mitigation.
- Efficient and Scalable AI: Novel neural architectures, efficient attention mechanisms, transformers, state-space models, and recurrent networks; model compression, pruning, quantization, neural architecture search, parameter-efficient fine-tuning, and efficient training and inference. Research also includes on-device AI, edge-cloud learning, distributed training, hardware-aware optimization, and compiler and kernel optimizations.
- Learning, Perception, and Embodied AI: Self-supervised, reinforcement, imitation, contrastive, and continual learning; few-shot learning, personalization, domain adaptation, and uncertainty estimation. Applications include computer vision, 3D perception, neural rendering, speech AI, autonomous driving, robotics, embodied intelligence, and human-AI interfaces.
Depending on the research project, internship responsibilities may include:
- Conducting original research, developing novel machine learning algorithms and architectures, and designing, training, and evaluating AI models to advance the state of the art.
- Developing efficient AI systems and software frameworks, including optimization for mobile, edge, and cloud platforms.
- Exploring emerging computing paradigms, including hardware-software co-design, compute-in-memory, and distributed or federated learning.
- Collaborating with researchers and engineers to prototype, validate, and communicate research findings, with opportunities to contribute to scientific publications and technology transfer.
Minimum Qualifications:
- Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
- 6+ months of experience developing and/or optimizing machine learning models, systems, platforms, or methods.
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 :
$178,200.00 - $267,400.00The 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 > Machine Learning ResearcherGeneral Summary:
Qualcomm AI Research is seeking world-class researchers to help push the boundaries of artificial intelligence and machine learning. Our team pioneers new algorithms, models, and systems that advance the state of the art while delivering exceptional performance with unprecedented power, memory, and computational efficiency.
Our multidisciplinary team brings together expertise across algorithms, software, hardware, and systems. We pursue fundamental and applied research, from foundational theories and novel learning algorithms to efficient AI systems deployed on resource-constrained devices. Working closely with Qualcomm's business and engineering teams, we translate research breakthroughs into technologies deployed worldwide across mobile, compute, automotive, robotics, cloud, XR, and IoT platforms, while publishing at leading AI conferences.
Our team has demonstrated world-first research breakthroughs and proof-of-concepts across model efficiency, representation learning, perception and understanding, generative and foundation models, reasoning and agentic intelligence, and embodied and physical AI. Our research contributions have earned numerous best paper awards, major research competition wins, and top rankings on AI and computer vision benchmarks. We also translate these breakthroughs into highly optimized AI models, end-to-end workflows, and developer tools for Qualcomm platforms, making many innovations accessible to all. Explore our research and innovations:
- Research Breakthroughs and Demonstrations
- Qualcomm AI Research Publications and Innovations Qualcomm AI Hub: Optimized Models and Workflows
Role Responsibilities:
Research interns will contribute to fundamental and applied research in artificial intelligence and machine learning, developing novel algorithms, models, and systems that advance the state of the art. Research opportunities span a broad range of areas, including:
- Generative AI and Foundation Models: Large language models (LLMs), multimodal foundation models, vision-language models (VLMs), vision-language-action models (VLAs), world models, and generative modeling for language, image, video, audio, and 3D content. Research topics include diffusion and autoregressive models, mixture-of-experts, parallel decoding, long-context modeling, and knowledge distillation.
- Agentic AI and Reasoning: Autonomous agents, multi-agent systems, reasoning, planning, and verification; memory management, retrieval-augmented generation (RAG), inference-time optimization, robustness, alignment, AI safety, and hallucination mitigation.
- Efficient and Scalable AI: Novel neural architectures, efficient attention mechanisms, transformers, state-space models, and recurrent networks; model compression, pruning, quantization, neural architecture search, parameter-efficient fine-tuning, and efficient training and inference. Research also includes on-device AI, edge-cloud learning, distributed training, hardware-aware optimization, and compiler and kernel optimizations.
- Learning, Perception, and Embodied AI: Self-supervised, reinforcement, imitation, contrastive, and continual learning; few-shot learning, personalization, domain adaptation, and uncertainty estimation. Applications include computer vision, 3D perception, neural rendering, speech AI, autonomous driving, robotics, embodied intelligence, and human-AI interfaces.
Depending on the research project, internship responsibilities may include:
- Conducting original research, developing novel machine learning algorithms and architectures, and designing, training, and evaluating AI models to advance the state of the art.
- Developing efficient AI systems and software frameworks, including optimization for mobile, edge, and cloud platforms.
- Exploring emerging computing paradigms, including hardware-software co-design, compute-in-memory, and distributed or federated learning.
- Collaborating with researchers and engineers to prototype, validate, and communicate research findings, with opportunities to contribute to scientific publications and technology transfer.
Minimum Qualifications:
- Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
- 6+ months of experience developing and/or optimizing machine learning models, systems, platforms, or methods.
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 :
$178,200.00 - $267,400.00The 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 .
Deep Learning Researcher Jobs by Experience Level
See All 56 Deep Learning Researcher Jobs
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Find Deep Learning Researcher JobsDeep Learning Researcher Job Market
Who's Hiring
- NVIDIA24
- Bot Auto4
- DoorDash2
- Quidient2
- Hayden AI2
Top Industries Hiring
- Technology & Software20
- Manufacturing2
- Science & Research2
- Artificial Intelligence2
- Aerospace & Defense1
What Employers Look For
The qualifications that appear most often in deep learning researcher jobs.
- PhD or Master's degree in computer science, machine learning, or a related field
- Strong proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
- Experience designing, training, and evaluating neural network architectures at scale
- Demonstrated research output such as peer-reviewed publications or conference papers
- Familiarity with distributed training techniques and large-scale GPU cluster workflows
- Solid foundation in linear algebra, probability, statistics, and optimization theory
Tips for Your Deep Learning Researcher Job Search
Lead your resume with published work
Hiring managers for deep learning researcher roles scan for papers, preprints, and open-source contributions before reading your work history. List your top publication or project in the first third of your resume so it lands above the fold.
Match your skills to the lab's architecture stack
Job postings often specify PyTorch versus JAX, or Transformer versus diffusion model experience. Tailor your resume to mirror the exact frameworks and model families named in each listing so your application clears automated screening.
Apply early to roles that fit
Migrate Mate lists deep learning researcher openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target postings by research area, not just title
Many deep learning researcher openings are posted under titles like applied scientist, ML research engineer, or AI research scientist. Search by research area, such as computer vision or speech, to surface relevant roles your title-only search would miss.
Prepare a system design answer for large-scale training
Interviewers at companies running large model training routinely ask how you would distribute a training run across hundreds of GPUs. Prepare a concrete answer covering data parallelism, gradient checkpointing, and your reasoning for each design choice.
Negotiate compute access, not only compensation
Deep learning researchers often find that GPU cluster allocation and cloud compute budgets affect their work more than base salary differences between offers. Ask directly what compute resources you would have access to before accepting any offer.
Deep Learning Researcher Jobs: Frequently Asked Questions
Which companies are hiring the most deep learning researchers?
The most active employers for deep learning researchers right now are NVIDIA, Bot Auto, and DoorDash, and the most openings are in California, Texas, and Massachusetts, based on current listings on Migrate Mate as of November 2026. Roles at large technology companies and AI-focused startups make up the bulk of active postings.
How many deep learning researcher jobs are remote?
About 27% of deep learning researcher openings are fully remote or hybrid as of November 2026, reflecting strong demand for research talent regardless of location. Roles focused on theoretical research, algorithm development, and model evaluation tend to offer the most remote flexibility, while positions requiring hands-on hardware access or lab collaboration are more likely to be on-site.
How do you become a deep learning researcher?
Start by building a strong foundation in linear algebra, calculus, and probability, then work through core machine learning theory before moving into neural network architectures. Complete a graduate degree or replicate published research independently to develop original project work. Contributing to open-source projects and posting preprints or workshop papers gives hiring teams concrete evidence of your research ability.
Can you get hired as a deep learning researcher without much experience?
Entry-level deep learning researcher roles do exist, particularly at companies with structured research programs or at startups willing to mentor candidates with strong academic foundations. The most effective path without industry experience is producing a public research artifact, such as a replication paper, a novel architecture experiment, or a well-documented open-source model, that demonstrates you can run a research cycle from hypothesis to result.
What does the deep learning researcher interview process look like?
Most deep learning researcher interview processes begin with a recruiter screen followed by a technical phone interview covering machine learning fundamentals and coding. Later rounds typically include a research presentation where you walk through past work in depth, one or more system design sessions focused on training pipelines or model deployment, and final interviews with research leads assessing scientific judgment and collaboration style.
Where can I find and apply to deep learning researcher jobs?
You can find and apply to deep learning researcher jobs on Migrate Mate, which lists current openings from across the United States in one place. Search for roles that match your research area and experience level, then apply directly to each listing that fits.
See All 56 Deep Learning Researcher Jobs
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