Software Engineer - Machine Learning For EDA Systems

General Summary:

Minimum Experience: 2+ years in software development

Role Overview

We are looking for a seasoned Software developer with 2-5 years experience in designing, developing, deploying, and scaling software platforms in the realm of Electronic Design Automation (EDA). You will work in cutting-edge initiatives that fuse Machine Learning with semiconductor design, driving robust systems that transform chip development workflows.

Minimum Qualifications:

Key Responsibilities

• Design and develop end-to-end ML-integrated software platforms built for scale, performance, and adaptability.
• Strong software development skills with experience in training and productizing Machine learning models, fostering innovation and engineering excellence.
• Good software design skills, knowledge of software development life cycle, embedding best development practices and agility across teams.
• Help in advanced software algorithm design tailored for automation and optimization in EDA flows.
• Engineer reliable and scalable data pipelines to fuel ML model development and inference.
• Knowledge of full-stack deployment strategies, enabling ML applications to function across diverse environments.
• Establish and maintain comprehensive ML Ops infrastructure, supporting continuous training, deployment, and monitoring.
• Experience with CI/CD pipelines, quality assurance standards, and system scalability from prototype to production.
• Ensure reliability and scalability of large system deployments for high-performance compute platforms.

Required Skills & Experience

• At least 2+ years of experience in software development, with a focus on building and maintaining scalable machine learning projects.
• Strong coding chops in one or more programming languages - Python , C++, Typescript and frameworks like TensorFlow, PyTorch, or Scikit-learn with knowledge of software development tools and best practices.
• Solid grasp of CI/CD tools (e.g. GitLab, Jenkins) and working knowledge on MLOps platforms (e.g., MLflow, Kubeflow, Airflow)
• Handson in various databases and skilled in data engineering and cloud/on-prem infrastructures (AWS, GCP, Kubernetes).
• Sharp communication skills with a track record of cross-functional collaboration.

Preferred Qualifications

• MS or PhD in Computer Science, Electrical Engineering, or a related field.
• Strong software coding and software design skills in Python / C++ . Should be aware of best software development practices, frameworks and tools.
• Knowledge in advanced ML techniquese.g., graph neural networks or reinforcement learning, Generative AI is preferred.
• Contributions to open-source, patents, or technical publications related to ML-driven design automation.
• Knowledge of EDA tools and flows is preferrable, including experience with platforms such as Synopsys, Cadence, or Siemens.