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
