AI ML Principal Engineer

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 8+ years of Hardware Engineering or related work experience.

OR

Master's degree in Computer Science, Electrical / Electronics Engineering, Engineering, or related field and 7+ years of Hardware Engineering or related work experience.

OR

PhD in Computer Science, Electrical / Electronics Engineering, Engineering, or related field and 6+ years of Hardware Engineering or related work experience.

Core Technical Expertise :

Strong software development experience (software engineering principles, algorithms, and data structures) with proficiency in Python.

Strong foundations in mathematics for ML and ML Algorithms (regression, tree ensembles, SVMs, clustering, time series), feature selection (PCA, mutual information), and model interpretability.

Hands-on experience with deep learning architectures (CNNs, RNNs, LSTMs, Transformers), training optimization (regularization, gradient clipping, learning rate scheduling), and advanced loss functions (contrastive, triplet).

Ability to break down design requirements and propose innovative, scalable solutions.

o Additional Expertise

Exposure to generative AI & LLMs : Experience with prompt engineering, RAG, parameter-efficient finetuning, context management, and LLM evaluation frameworks.

Good understanding of VLSI Design Execution - with development experience on PnR or Synthesis or STA

Tooling & Infrastructure : Proficient in Python, PyTorch / TensorFlow, Scikit-learn, Pandas, NumPy

16+ years experience required

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