Staff Machine Learning Engineer
Role details
Job location
Tech stack
Job description
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Stay current with state-of-the-art research in Machine Perception (computer vision, machine learning, LLMs, world models, and related areas).
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Research relevant papers and design, run, and evaluate experiments.
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Define and drive perception performance KPIs (e.g., accuracy, latency, memory), including work on neural architecture search, quantization, and algorithmic improvements.
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Partner with Product and Development teams to provide input on deploying ML models into production.
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Collaborate with Hardware teams to provide technical feedback that informs future hardware decisions., 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.
Requirements
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6+ years of relevant industry experience.
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Strong background in computer vision and deep learning (e.g., detection, segmentation, tracking, 3D perception).
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Excellent Python software engineering skills.
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Expertise in PyTorch (or equivalent) and modern CV architectures (CNNs, Transformers).
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Proven production ML experience, including training, evaluation, deployment, and monitoring of CV models.
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Experience optimizing models for latency, memory, and quality, especially for edge or resource-constrained systems.
Preferred Qualifications
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Solid C++ experience for performance-critical components.
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Experience with 3D vision and multi-modal perception (depth, point clouds, sensor fusion).
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Model and inference optimization experience (quantization, TensorRT, ONNX, edge deployment).
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Familiarity with distributed training and MLOps (CI/CD, experiment tracking).
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Domain experience in XR, robotics, or real-time systems., * 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., 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.
*References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.