18 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Design, develop, train, optimize, evaluate, and deploy machine learning and deep learning models.
- Perform data collection, preprocessing, feature engineering, and model evaluation.
- Develop AI solutions for prediction, optimization, automation, and analytics.
- Integrate AI solutions into production environments with software, data, and domain experts.
- Research emerging AI technologies and evaluate their applicability.
- Prepare technical documentation, reports, and stakeholder presentations.
Requirements
- M.Tech in Artificial Intelligence, Machine Learning, Computer Science, Data Science, Electrical Engineering, or a related discipline.
- At least 2 years of experience; fresh M.Tech graduates may also apply.
- Strong understanding of machine learning, deep learning, generative AI, and large language models.
- Proficiency in Python and AI/ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
- Knowledge of data structures, algorithms, and software engineering practices.
- Preferred experience includes generative AI, RAG pipelines, LLM fine-tuning, AI agents, NLP, computer vision, or reinforcement learning.
- Familiarity with model deployment, MLOps, cloud platforms, Git, Docker, Kubernetes, and CI/CD workflows is preferred.
- Publications, academic projects, or internships in AI/ML are desirable.
- Strong analytical, problem-solving, communication, collaboration, and independent-working abilities.
Benefits
- Full-time employment.
- Qualcomm provides reasonable accommodations during the application and hiring process for applicants with disabilities.
Tech Stack
Categories
About Qualcomm
Qualcomm is a public semiconductor company headquartered in San Diego, founded in 1985, that designs and sells wireless chipsets and platforms for mobile devices, automotive, IoT, and networking, notably the Snapdragon application processors and 5G modems. It also licenses a large portfolio of cellular patents to device makers, generating revenue alongside chip sales; its technology underpins many Android smartphones and emerging automotive and edge-compute systems, and it trades on NASDAQ as QCOM.