Why This Role Stands Out
You'll have the opportunity to pioneer groundbreaking GenAI solutions for cutting-edge wireless and media platforms, significantly boosting engineering productivity and shaping the future of embedded software development at a renowned tech leader. This hybrid role is ideal for a mid-senior engineer with strong embedded C/C++ and Python skills, coupled with expertise in GenAI and MLOps, who thrives in a collaborative, innovation-driven environment. Embrace this chance to grow your skills, make a tangible impact, and contribute to a company at the forefront of technology.
Quick Overview
Job Description
Qualcomm seeks a Gen AI Transformation Engineer to accelerate embedded software and engineering productivity for next gen wireless and media platforms. You will design and deploy GenAI solutions across firmware, embedded OS, and toolchains to automate workflows, optimize code, and enhance developer experience. Partner with software, silicon, and DevOps teams to integrate AI copilots, code analysis, and test generation into existing pipelines. Evaluate models, build scalable inference services, measure impact on productivity, and drive best practices for secure, compliant AI adoption in a fast paced, innovation driven environment.
Responsibilities
- Design and implement Gen
- AI solutions to enhance embedded software development and engineering productivity
- Integrate AI copilots, code generation, and static analysis tools into existing CI/CD and development workflows
- Collaborate with embedded, firmware, tools, and Dev
- Ops teams to identify and automate high value engineering use cases
- Build and maintain scalable Gen
- AI services and APIs optimized for Qualcomm hardware and software stacks
- Evaluate and fine tune large language models and domain specific models for code and documentation tasks
- Develop metrics and dashboards to measure productivity, quality, and performance impact of AI solutions
- Ensure AI systems follow security, privacy, and responsible AI guidelines and Qualcomm standards
- Create technical documentation, best practices, and internal training for AI augmented engineering workflows
Required Skills
- Embedded software development
- C/C++ programming
- Python programming
- Machine learning and Gen
- AI (LLMs)
- Model integration and APIs (REST/GRPC)
- CI/CD pipelines and Dev
- Ops tooling
- Cloud platforms (AWS, Azure, or GCP)
- MLOps and model monitoring
- Software architecture and design
- Data engineering and feature pipelines
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