Qualcomm Recruitment 2026 | AI/ML Performance Engineer | Bangalore

Qualcomm Off Campus 2026:

What an AI/ML Engineer at Qualcomm actually does:

• Analyze and optimize AI and Machine Learning workloads on Neural Processing Units (NPU), Neural Signal Processors (NSP), and GPUs

• Identify and resolve performance bottlenecks related to compute resources, memory bandwidth, latency, DMA, NoC, SMMU, and scheduling.

• Drive optimizations for latency‑critical inference, high‑throughput pipelines, and concurrent multi‑VM execution.

• Conduct roofline analysis, utilization studies, and memory access optimization using hardware performance counters.

• Benchmark and optimize CNNs, Transformers, VLMs, and diffusion models for real‑world and customer use cases.

• Optimize model execution using operator fusion, graph partitioning, quantization, mixed precision, tiling, and batching.

• Collaborate with software teams to optimize drivers, runtimes, memory allocation, power consumption, thermal management, and QoS performance.

• Analyze performance under concurrent, virtualized, and safety‑critical or real‑time environments.

• Build and maintain performance benchmarking tools, profilers, regression frameworks, and micro-benchmark suites.

• Partner with architecture, compiler, SDK, and AI framework teams to influence HW/SW design and resolve performance escalations.

Qualcomm Eligibility Criteria:

• Bachelor’s degree in
  – Computer Science Engineering
  – Information Systems
  – Related field

• 1+ years of
  – Hardware Engineering
  – Software Engineering
  – Systems Engineering
  – Related work experience.

Required skills:

• Software development with exposure to AI coding tools and excellent analytical, development, and problem-solving skills.
• Embedded software (Linux, Android, RTOS)
• Experience in system performance domain with a focus on neural accelerators and GPUs
• Knowledge of CPU, NPU, GPU,  NOC, DDR architecture
• Machine Learning fundamentals
• Knowledge  in neural network quantization, compression, pruning algorithms, deep learning kernel/compiler optimization
• Strong communication skills.

Who should apply for Qualcomm:

Apply if:

• Understand hardware acceleration technologies such as GPUs and NPUs.

• Enjoy solving complex system performance challenges.

• Interested in embedded systems, AI computing, and next-generation hardware

Don’t apply if:

• Do not have a background in Computer Science, Electronics, AI, or Engineering
• Lack knowledge of AI/ML concepts and hardware architectures

• Prefer non-technical or business-oriented roles.

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Qualcomm Recruitment Selection Process:

The Company’s selection process is a structured series of stages designed to identify and hire the most suitable candidates for various roles within the company. Here is an overview of the typical selection process:

1. Online Application
2. Resume Screening
3. Online Assessments
4. Technical Interviews
5. Offer
6. Background Check
7. Onboarding

The steps may vary depending on the role/ team

Why Join Qualcomm?

• Competitive salary packages

• Comprehensive health and wellness programs

• Flexible work schedules

• Career development and technical training

• Global learning opportunities

• Performance-based rewards and bonuses

• Parental support programs

• Employee assistance programs

• Collaborative engineering culture

• Exposure to next-generation AI hardware and software technologies