Qualcomm Staff/Lead Engineer - Wireless R&D MLOps 

India, Karnataka, Bengaluru 

945833262

Job Area:

Engineering Group, Engineering Group > Systems Engineering

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Systems Engineer, you will research, design, develop, simulate, and/or validate systems-level software, hardware, architecture, algorithms, and solutions that enables the development of cutting-edge technology. Qualcomm Systems Engineers collaborate across functional teams to meet and exceed system-level requirements and standards.

Minimum Qualifications:

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.

Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience.

PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.

Job Overview:

We are looking for an individual who is passionate about system design and can work closely with data scientists, HW, SW, and test teams to deliver end to end solutions. The role requires ability to build a production/deployment system for bridging the gap between data science and lifecycle management of machine learning models for Wireless world. Conceptualize new solutions that will operationalize and scale machine learning models for Wireless networks/Cellular chipsets and standards, propose implementation details, evaluate and simulate performance benefits, and analyze and diagnose system level issues, collaborate across functional teams to meet and exceed system-level requirements and standards.

Minimum Qualifications:

• Master’s degree in engineering, Information Systems, Computer Science, or related fields.

• 4+ years of Systems Engineering, or data engineering, or software development, or DevOps/MLOps or related work experience.

• Strong hands-on expertise in machine learning concepts and frameworks (e.g., PyTorch, TensorFlow).

• Hands-on expertise in automating ML model deployment, monitoring, and management. Aware of best practices for data versioning, model training, and experimentation.

• 4+ years of experience with Programming Language such as C/C++/Java, or Python.

• Experience in creating versatile tools and frameworks using Python, and knowledge of AWS analytical technologies and related resources (Glue, Athena, QuickSight, SageMaker, etc.)

• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud), databases, data warehousing, data streaming frameworks (e.g., Apache Kafka/ SQL), containerization technologies and orchestration tools (e.g., Docker, Kubernetes) will be added advantage.

Preferred Qualifications:

• Academic project experience or 4+ year industry experience in at least one or more of the following areas: MLOps engineering or related areas, applied mathematics, machine learning or Bayesian inference, architecture/systems engineering, information theory.

• Experience in developing and maintain CI/CD pipelines for machine learning models. Model monitoring and retraining.

• Experience in state-of-the-art methods to interpret/analyze data, identify patterns/trends/ insights, and tuning/optimization of models.

• Forward looking attitude, analyze upcoming trends in neural NWs (GNN, GenAI, etc) and techniques.

• Strong in mathematical statistics, probability theory and Linear algebra related to Machine Learning / Deep Neural NWs.

• Strong analytical and problem-solving skills.

• Strong hands-on in Data structures and algorithms.

• Good understanding of design patterns and design philosophies.

• Passion for learning and intellectual curiosity.

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.