Software Engineer
Responsibilities
Qualifications & Requirements
Experience Level: Mid Level
Full Job Description
Qualcomm India Private Limited is seeking a talented Software Engineer specializing in Machine Learning for Electronic Design Automation (EDA) Systems in Bengaluru / Bangalore, India. This role offers an exciting opportunity to work on cutting-edge initiatives that merge Machine Learning with semiconductor design, driving innovation and transforming chip development workflows.
We are looking for a seasoned software developer with 2-5 years of experience in designing, developing, deploying, and scaling software platforms within the EDA domain. You will be instrumental in developing end-to-end ML-integrated software platforms, training and productizing machine learning models, and engineering reliable and scalable data pipelines.
Key responsibilities include contributing to advanced software algorithm design for automation and optimization in EDA flows, implementing full-stack deployment strategies for ML applications, and establishing and maintaining robust ML Ops infrastructure. Experience with CI/CD pipelines, quality assurance standards, and system scalability from prototype to production is essential. Ensuring the reliability and scalability of large system deployments for high-performance compute platforms is also a core part of this role.
Required skills include at least 2+ years of software development experience with a focus on scalable machine learning projects, strong coding proficiency in Python, C++, or Typescript, and familiarity with frameworks like TensorFlow, PyTorch, or Scikit-learn. Knowledge of CI/CD tools (e.g., GitLab, Jenkins) and MLOps platforms (e.g., MLflow, Kubeflow, Airflow) is crucial. Experience with databases, data engineering, and cloud/on-prem infrastructures (AWS, GCP, Kubernetes) is also highly valued.
Preferred qualifications include an MS or PhD in Computer Science or Electrical Engineering, advanced ML techniques (e.g., graph neural networks, reinforcement learning, Generative AI), contributions to open-source projects, patents, or technical publications, and knowledge of EDA tools and flows (Synopsys, Cadence, Siemens).