Company:
Qualcomm India Private Limited
Job Area:
Engineering Group, Engineering Group > Hardware Engineering
General Summary:
As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Hardware Engineer, you will plan, design, optimize, verify, and test electronic systems, bring-up yield, circuits, mechanical systems, Digital/Analog/RF/optical systems, equipment and packaging, test systems, FPGA, and/or DSP systems that launch cutting-edge, world class products. Qualcomm Hardware Engineers collaborate with cross-functional teams to develop solutions and meet performance requirements.
Minimum Qualifications:
• Bachelor's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 3+ years of Hardware Engineering or related work experience.
OR
Master's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 2+ years of Hardware Engineering or related work experience.
OR
PhD in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 1+ year of Hardware Engineering or related work experience.
Our team is focused on applying state-of-the-art AI and ML technologies to solve complex business problems in the chip design, qualification, and debug engineering processes. We aim to enhance engineering efficiency through intelligent automation, data-driven insights, and innovative tool development.
This role focuses on building scalable cloud-native AI applications that enhance engineering productivity. You’ll work on distributed systems, cloud platforms, and user-facing tools that integrate AI/ML capabilities into chip design and debug workflows.
Key Responsibilities
Design and implement AI/ML applications and pipelines using LLMs, GenAI platforms, and custom models to address real-world engineering challenges.
Build intelligent agents and user interfaces that integrate seamlessly into engineering workflows.
Develop robust data ingestion, transformation, and analysis pipelines tailored to chip design and debug use cases.
Build distributed computing architectures and scalable backend services.
Design intuitive user interfaces and intelligent agents for engineering teams.
Implement robust ETL pipelines and integrate with SQL/NoSQL databases.
Collaborate with team leads to ensure timely delivery and high-quality solutions.
Provide technical support and training to internal teams, helping resolve issues and improve adoption.
Engage in cross-functional initiatives to solve technical problems across departments.
Continuously contribute to the innovation and evolution of tools, technologies, and user experiences.
Minimum Qualifications:
Bachelor’s degree in Computer Science
Very Strong in data structures, algorithms, and software design principles.
Strong programming skills in Python and C/C++.
Experience in building scalable software systems and solving complex technical problems.
Experience with software architecture and design patterns.
Fast learner with a strong technical foundation and ability to work independently.
Very Strong Analytical and problem Solving Skill.
Preferred Qualifications:
Master’s degree in Computer Science or related field.
Proficiency in data analysis using Python libraries (e.g., Pandas, NumPy, Matplotlib).
Familiarity with SQL databases, ETL frameworks, and cloud platforms (e.g., AWS).
Hands-on experience on Cloud Scale & Distributed Computing Architectures.
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Hands-on experience with AI/ML technologies including:
Supervised and unsupervised learning
LLMs, GenAI platforms, and RAG optimization
ML frameworks like scikit-learn, PyTorch, TensorFlow
LLM integration frameworks (e.g., LangChain)
Keywords: Cloud Computing, AI, GenAI, LLM, AWS, LangChain, ETL, Distributed Systems, Big Data Analytics, SW Engineering, Algorithm, SQL
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