Machine Learning Engineer (New Grad)

About This Role

Qualcomm is hiring Machine Learning Engineers from campus to work on AI that runs on Snapdragon-powered devices — smartphones, laptops, cars, and IoT products used by billions of people. You will build and optimize ML models that execute on Qualcomm's Hexagon DSP and AI Engine NPU hardware.

Job Overview

• Job Title: Machine Learning Engineer (New Grad)
• Company: Qualcomm
• Location: San Diego, CA / Santa Clara, CA / Raleigh, NC / Austin, TX / Boxborough, MA
• Job Type: Full-time
• Experience Level: Entry-level (0–2 years)
• Salary Range: $36–$50/hr
• Posted Date: 2026-06-01
• Application Deadline: 2026-07-01

Role Context

Qualcomm's AI teams focus on edge AI — running high-quality models within tight power and memory budgets. New grad MLEs work on model compression, quantization pipelines, and the AIMET model optimization toolkit. You will collaborate with hardware architecture engineers to make the most of Qualcomm's specialized AI accelerators.

Key Responsibilities

• Design and optimize ML models for on-device inference on Qualcomm AI Engine
• Apply quantization, pruning, and knowledge distillation using AIMET and PyTorch
• Build and maintain model benchmarking pipelines across Snapdragon hardware targets
• Collaborate with hardware teams to leverage new NPU features in software
• Support OEM and developer partners in deploying AI models to Qualcomm-powered devices
• Contribute to internal tools and documentation for the AIMET open-source project

Requirements & Skills

• Bachelor's or Master's in ECE, CS, or a related field (2024–2025 grad)
• Solid ML fundamentals and hands-on PyTorch experience
• Interest in model efficiency, quantization, or hardware-aware deep learning
• C or C++ programming knowledge is a plus
• Familiarity with ONNX, TFLite, or other model exchange formats
• Strong attention to accuracy-efficiency trade-offs in ML model design

Benefits & Work Conditions

• $36–$50/hr with Qualcomm RSUs and annual performance bonus
• Hybrid schedule with flexible remote days
• Access to Snapdragon hardware for development and benchmarking
• Comprehensive health, dental, and vision insurance
• $3,000 annual education and conference reimbursement

Who Should Apply

Graduates who are excited about edge AI — making powerful models run efficiently on real devices, not just cloud servers. If you enjoy the challenge of fitting a state-of-the-art model into a mobile power budget, Qualcomm is the most hardware-focused ML environment in the industry.

About the Company

Qualcomm designs the Snapdragon chips found in the majority of Android smartphones and a growing share of laptops, AR headsets, and automotive platforms. Its AI research and engineering teams are global leaders in on-device AI inference and mobile neural network optimization.

How to Apply

Apply via Qualcomm Careers. Search "Machine Learning Engineer New Grad." The process includes an online coding challenge, a technical screen on ML and systems, and a virtual loop with team engineers.