Engineer/ Sr Engineer/ Lead Sr Enginner, AI Platform Development

3 - 8 years

25 - 30 Lacs

Posted:2 weeks ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

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. ORMaster's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 2+ years of Hardware Engineering or related work experience. ORPhD 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. Youll 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:

  • Bachelors 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:

  • Masters 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.
  • 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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Qualcomm

Technology

San Diego

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