Overview

As a leading technology innovator, Qualcomm is shaping next-generation intelligent and connected experiences. We are seeking multiple highly skilled Machine Learning & Data Science Engineers who can independently drive end-to-end development of scalable data pipelines, ML/NLP models, and production-grade Python systems. These roles require strong technical depth across Machine Learning, NLP, Data Engineering, and Python backend development, along with the ability to work autonomously and deliver high-impact solutions.

Responsibilities

• Develop, fine-tune, and deploy ML and NLP models using TensorFlow, PyTorch, and Scikit-learn
• Apply advanced NLP methods including Transformers, BERT-based models, and LLM fine-tuning
• Build Retrieval-Augmented Generation (RAG) pipelines using LangChain, LlamaIndex, FAISS, Milvus, etc.
• Design and implement scalable ETL and data ingestion pipelines using SQL, NoSQL, and big data frameworks (Spark, Hadoop, PySpark)
• Build efficient data models, schema designs, and storage strategies (PostgreSQL, MongoDB, Cassandra, etc.)
• Ensure data quality, validation, and governance across distributed systems
• Own documentation and architecture of data flows
• Develop scalable backend components and services using Python (FastAPI, Flask, Django)
• Automate workflows, model pipelines, and data processing using Pandas, NumPy, SQLAlchemy
• Integrate ML solutions into production systems with clean, modular, well-documented code
• Work independently to design, build, and deliver complete ML/Data solutions
• Partner with cross-functional teams including systems, hardware, architects, and test teams
• Translate business requirements into technical approaches and drive execution

Qualifications

• Bachelor's/Master's degree in Computer Science, Engineering, or relevant field
• 1-3 years of experience across ML, NLP, and Data Engineering
• Expert-level Python programming with hands-on experience in backend/API development
• Strong knowledge of ML/NLP algorithms, LLMs, and RAG frameworks
• Proficiency in SQL and familiarity with SQL/NoSQL databases
• Experience with big data tools such as Spark or Hadoop
• Experience with cloud platforms (AWS, Azure)
• Strong communication, analytical, and problem-solving skills
• Ability to work independently and take end-to-end ownership of solutions

Nice to have

• Experience with model registries and cloud ML environments (HuggingFace, AWS Sagemaker, Azure ML)

Education

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