Develop AI, LLM, ML and statistical based solutions to build state-of-the-art predictive, prescriptive , optimization and automation , pattern-mining solutions for silicon design verification and firmware validation Collaborate with cross-functional teams to ensure the accuracy, reliability, and performance of semiconductor products. Participate in end-to-end project scoping and stakeholder discussions to determine technical merit of the idea, vale proposition and resource requirements. Education: Master's or PhD in Computer Science, Electrical Engineering, or a related field. Experience: 12+ years in data science and machine learning. Experience in silicon verification or semiconductors in general is highly desirable. In-depth understanding statistics, classical ML algorithms, neural networks and in-depth understanding of algorithms and formulation behind LLM, RAG and agents. Hands on experience and solid understanding of data engineering and building deployment pipelines for solutions built. Be able to extract, process and clean data using known frameworks. Proficiency in programming languages such as Python, R, and SQL. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and data visualization tools (e.g., Tableau, Power BI). Ability to scope projects, develop project plan and lead, execute, and deliver as per the plan. Ability to understand the customer pain point and find appropriate solutions to address the problem. Strong passion and attitude to work in semiconductor industry delivering high value and high impact data science solutions. Attitude and temperament for team-work, mentoring, learning, ethics and professional communication.
