Sr. AI Engineer

Qualcomm; Santa Clara (CA); On-site; USD 129,300 - 193,900; Full time

Benefits offered by this job

Comprehensive healthcare

Retirement plans

Annual discretionary bonus program

RSU grants

Job summary

Qualcomm is seeking an AI Model Training Engineer to design and optimize machine learning models. You will collaborate with data scientists and engineers to ensure models meet performance and ethical standards.

The ideal candidate should have a strong background in programming, machine learning frameworks like PyTorch, and best practices in training models. A degree in a relevant field and a minimum of 2 years of experience are required. This role offers competitive benefits and a base salary range of $129,300 – $193,900.

Qualifications

• 2+ years of work experience with programming languages such as C, C++, Java, Python.
• Experience with training machine learning models.
• Understanding of training best practices and ethical AI practices.

Responsibilities

• Design, train, fine-tune, and optimize machine learning models.
• Collaborate with data engineering teams to ensure high-quality datasets.
• Monitor training processes and address overfitting or underfitting.

Skills

Machine learning

Deep learning

Python

C/C++

Data science

MLOps

Education

Bachelor's degree in Engineering, Computer Science, or related field

Master's degree in Engineering, Computer Science, or related field

PhD in Engineering, Computer Science, or related field

Tools

PyTorch

Hugging Face Transformers

NumPy

scikit-learn

Job description

Company

Qualcomm Technologies, Inc.

Job Area

Engineering Group, Engineering Group > Software Engineering

General Summary

We are looking for a skilled and motivated AI Model Training Engineer to join our team. In this role, you will be responsible for designing, training, fine‑tuning, and optimizing machine learning models for a range of applications. You’ll work closely with data scientists, researchers, and infrastructure engineers to develop robust, scalable models that meet performance, efficiency, and ethical standards.

Key Responsibilities

• Build and train machine learning and deep learning models using structured and unstructured datasets.
• Fine‑tune pre‑trained models (e.g., object detection, classification, LLMs, vision transformers) for specific downstream tasks.
• Design training pipelines with reproducibility, efficiency, and scalability in mind.
• Conduct hyperparameter optimization, model evaluation, and performance tuning.
• Collaborate with data engineering teams to ensure high‑quality, well‑labelled, and balanced datasets.
• Monitor training processes, identify failure modes, and address overfitting, underfitting, or bias.
• Keep up to date with the latest research and integrate state‑of‑the‑art techniques into training workflows.
• Document models, training strategies, and experiments for internal knowledge sharing and compliance.

Minimum Qualifications

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

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or related field.
• Solid experience training machine learning models with frameworks like PyTorch, onnxruntime or Hugging Face Transformers.
• Proficient in Python and familiar with ML libraries such as PyTorch, scikit‑learn, and NumPy.
• Understanding of training best practices, including dataset management, batching, checkpointing, and loss functions.
• Experience with GPU/TPU‑based training environments and distributed training frameworks (e.g., PyTorch, onnxruntime).
• Experience training large‑scale models (e.g., LLMs, 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.

EEO Employer

Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.

Pay range and Other Compensation & Benefits

Pay: $129,300.00 – $193,900.00. In addition to base salary, Qualcomm offers a competitive annual discretionary bonus program and opportunities for annual RSU grants. Benefits include comprehensive healthcare, retirement plans, and other services designed to support success at work, at home, and in the community.