AI/ML Commercialization Lead - Director, Engineering- CE

Company:Qualcomm India Private Limited
Job Area:Engineering Group, Engineering Group > Software Applications Engineering

General Summary:

Summary:
Role Overview
We are seeking a Director of AI/ML Engineering to lead the commercialization of production‑grade AI/ML and GenAI solutions across automotive and edge platforms. This role owns technical strategy, execution, and customer ownership for AI systems spanning LLMs, VLMs/LVMs, multimodal AI, and agentic frameworks, deployed on heterogeneous SoCs (CPU/GPU/DSP/NPU) under strict performance, safety, and reliability constraints.

The Director will shape the AI roadmap, build and scale high‑performing teams, partner with product, silicon, and customer engineering, and ensure delivery of differentiated, scalable AI capabilities across infotainment, digital cockpit, ADAS, industrial, and connected‑edge use cases.

Minimum Qualifications:

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 8+ years of Software Applications Engineering, Software Development experience, or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 7+ years of Software Applications Engineering, Software Development experience, or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 6+ years of Software Applications Engineering, Software Development experience, or related work experience.

• 4+ years of experience with Programming Language such as C, C++, Java, Python, etc.
• 4+ years of experience with debugging techniques.

Job Title:
Director – AI/ML Engineering (Automotive & Edge AI)
Location: Bengaluru, India
Employment Type: Full‑time

Key Responsibilities

• AI/ML Strategy & Platform Leadership
• Define and own the AI/ML technology roadmap aligned with business goals across automotive and edge AI platforms.
• Drive adoption of LLMs, VLMs/LVMs, multimodal AI, and agentic AI systems for real‑world, safety‑critical deployments.
• Influence platform and silicon‑level decisions by translating AI workload requirements into hardware and software capabilities.

Execution & Delivery

• Oversee end‑to‑end delivery of AI systems from research to production, including model onboarding, optimization, validation, and lifecycle management.
• Ensure performance, power, latency, memory, and accuracy targets are met across heterogeneous compute (CPU/GPU/DSP/NPU).
• Establish best practices for model optimization (quantization, compression, batching, KV‑cache tuning, mixed precision).

Team & Organizational Leadership

• Build, mentor, and scale multi‑disciplinary AI/ML engineering teams (ML engineers, systems engineers, platform engineers).
• Set technical direction, define career growth paths, and uphold a high bar for engineering excellence.
• Foster a culture of ownership, accountability, and innovation.

Cross‑Functional & Executive Collaboration

• Partner closely with Product Management, Silicon, SDK, Systems, Safety, and Customer Engineering teams.
• Act as an executive technical voice in customer engagements, escalations, and roadmap discussions.
• Translate complex technical topics into clear, actionable insights for senior leadership.

Safety, Quality & Compliance

• Ensure AI systems are designed with safety‑first principles, including alignment with ISO 26262, ASPICE, and functional‑safety expectations.
• Establish robust validation, observability, and governance frameworks for AI behavior in production.

Minimum Qualifications

• Bachelor’s degree in Engineering, Computer Science, or a related field.
• 25+ years of industry experience in software engineering.
• 20+ years of people management experience, including managing managers or senior technical leads and customers.
• Strong background in AI/ML system design, not just model development.
• Hands‑on experience with ML frameworks (PyTorch, TensorFlow, ONNX) and edge/embedded deployment.
• Proven ability to deliver large‑scale, production AI systems in complex environments

Preferred Qualifications

• Master’s or PhD in AI/ML, Computer Science, or related field.
• Deep understanding of LLMs, VLMs/LVMs, multimodal and agentic AI architectures.
• Experience with automotive or industrial platforms, embedded Linux/QNX, and real‑time constraints.
• Familiarity with QNN‑like runtimes, inference SDKs, and heterogeneous acceleration.
• Strong customer‑facing experience, including executive‑level technical discussions.
• Track record of influencing product and platform roadmaps through technical leadership.
• Experience in software architecture and design patterns
• Knowledge of architectural approaches for large-scale software applications
• Previous customer-facing experience is advantageous
• Exposure to fine-tuning GenAI models and reinforcement learning considered a plus
• Expertise in inference accuracy, throughput optimization, and edge deployment highly desirable
• Lead system-level problem triage to identify root causes and communicate testing/debugging results to relevant stakeholders

Applicants: 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).

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