Q

Qualcomm

Designs mobile chips and licenses wireless patents

Technical Lead - AI Systems & Architecture, Hardware Engineering

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • A Bachelor's or Master's degree in Computer Science, Data Science, or a related field, with at least 7 years of work experience.
  • Strong programming skills in Python or C++.
  • A solid understanding of data structures, algorithms, and software design principles.
  • Strong analytical and problem-solving skills.
  • Hands-on experience with supervised and unsupervised learning techniques, including classification, clustering, and dimensionality reduction.
  • Experience with deep neural network architectures, including recurrent neural networks and Transformers.
  • Experience with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch.
  • Experience with generative AI, large language models, retrieval-augmented generation optimization, large language model fine-tuning, and distillation.
  • Proficiency in data analysis using Pandas, NumPy, and Matplotlib.
  • Knowledge of statistical analysis and visualization, feature engineering, and model evaluation.
  • Understanding of GPUs, CUDA, and high-performance computing frameworks and methods.
  • A Bachelor's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or a related field and at least 4 years of Hardware Engineering or related work experience; or a Master's degree in those fields and at least 3 years of related experience; or a PhD in those fields and at least 2 years of related experience.

Responsibilities

  • Design and implement end-to-end data analytics workflows tailored to semiconductor engineering use cases.
  • Develop, train, and optimize machine learning models using supervised, unsupervised, and deep learning techniques.
  • Perform feature engineering, model evaluation, and hyperparameter tuning to improve model performance.
  • Build scalable data ingestion and transformation pipelines using Python and cloud-native tools.
  • Apply statistical analysis and visualization techniques to derive insights from large datasets.
  • Conduct time series analysis using methods such as ANOVA and other statistical techniques.
  • Experiment with generative AI platforms, large language models, and retrieval-augmented generation techniques to enhance model capabilities.
  • Collaborate with cross-functional teams to integrate machine learning models into engineering workflows and tools.
  • Document methodologies and provide technical guidance to internal teams.

Desired Qualifications

  • A PhD in Computer Science, Data Science, or a related field.
  • Experience developing and training large models from scratch.
  • Familiarity with time series analysis methods, including ANOVA, ARIMA, and seasonal decomposition.
  • Familiarity with SQL databases, ETL frameworks, and cloud platforms such as AWS.
  • Knowledge of large language model integration frameworks such as LangChain.
  • Hands-on experience with distributed computing and cloud-scale data processing.
  • Knowledge of software design and architecture.

About the Company

Qualcomm

Designs mobile chips and licenses wireless patents

Qualcomm designs the Snapdragon processors and modems inside many Android phones, and it licenses its wireless patents to device makers around the world. It helped commercialize CDMA, the cellular technology behind 3G networks, and its patents cover core parts of the 4G and 5G standards that phones use to connect. The company does not run its own chip factories; contract foundries make its chips, which it sells to makers of phones, PCs, cars, and connected devices. Device makers also pay Qualcomm royalties for using its patented technology, which forms a second business alongside chip sales. Qualcomm was founded in 1985 and is based in San Diego, California.

Company size
10,001+
Company stage
IPO
Headquarters
San Diego, CA
Founded
1985

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