Sr. AI Engineer

Qualcomm offers an onsite AI engineering role in Santa Clara, CA with a competitive annual salary range of USD 129,300 - 193,900 and additional compensation and benefits, including a competitive annual discretionary bonus program, the opportunity for annual RSU grants, and a highly competitive benefits package.

What you’ll do

As an AI Model Training Engineer, you will design, train, fine-tune, and optimize machine learning models that meet performance, efficiency, and ethical standards. You will work closely with data scientists, researchers, and infrastructure engineers to deliver robust, scalable model training outcomes.

• Build and train machine learning and deep learning models using structured and unstructured datasets.
• Fine-tune pre-trained models for downstream needs, including object detection, classification, LLMs, and vision transformers.
• Create training pipelines focused on reproducibility, efficiency, and scalability.
• Run hyperparameter optimization, perform model evaluation, and tune model performance.
• Collaborate with data engineering to support high-quality, well-labeled, balanced datasets.
• Monitor training runs, troubleshoot failure modes, and address overfitting, underfitting, or bias.
• Stay current with leading research and incorporate state-of-the-art techniques into training workflows.
• Document models, training strategies, and experiments to support internal knowledge sharing and compliance.

Key skills and requirements

• Bachelor’s degree in Engineering, Information Systems, Computer Science, or related field, plus 2+ years of Software Engineering or related work experience, or
• Master’s degree in the same fields, plus 1+ year of Software Engineering or related work experience, or
• PhD in the same fields.
• 2+ years of academic or work experience with programming languages such as C, C++, Java, or Python.

Technologies you’ll use

Work may include C, C++, Java, Python, PyTorch, onnxruntime, Hugging Face Transformers, scikit-learn, NumPy, GPU/TPU, and distributed training frameworks, along with LLMs, vision transformers, cloud-based ML platforms, CI/CD, containerization, model versioning, and MLOps.

Preferred qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or related field.
• Experience training machine learning models with PyTorch, onnxruntime, or Hugging Face Transformers.
• Proficiency in Python and familiarity with ML libraries such as PyTorch, scikit-learn, and NumPy.
• Understanding training best practices such as dataset management, batching, checkpointing, and loss functions.
• Experience with GPU/TPU-based training environments and distributed training frameworks (for example PyTorch or onnxruntime).
• Experience training large-scale models (for example LLMs or multimodal models) or using cloud-based ML platforms.
• Knowledge of MLOps practices including CI/CD, containerization, and model versioning.
• Background in performance profiling and memory optimization for training workflows.
• Exposure to ethical AI practices, including fairness, explainability, and model auditing.

Pay range and other compensation: $129,300.00 - $193,900.00