AI/ML Engineer

Qualcomm · Chennai · 1–3 yrs experience · Posted 2026-07-28

Tech stack: AWS, Azure, Cassandra, Django, FastAPI, Flask, MongoDB, PostgreSQL, Python, SQL

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About the role

Qualcomm India Private Limited
Engineering Group, Engineering Group > Software Engineering
Responsibilities: - 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.
- Machine Learning & NLP
- 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.
- Work with model registries and cloud ML environments (HuggingFace, AWS Sagemaker, Azure ML).
- Data Engineering & Infrastructure
- 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.
- Python Development 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.
- Collaboration & Ownership
- 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.
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field.

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

Responsibilities

- 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.
- Machine Learning & NLP
- 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.
- Work with model registries and cloud ML environments (HuggingFace, AWS Sagemaker, Azure ML).
- Data Engineering & Infrastructure
- 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.
- Python Development 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.
- Collaboration & Ownership
- 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.

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