Job Description:
- Natural Language Processing (NLP) / Large Language Models (LLMs): For interpreting text-based functional requirements and constraints, and for generating documentation and annotations.
- Computer Vision (CV) / Optical Character Recognition (OCR): If the input includes hand-drawn sketches or image-based diagrams, CV and OCR are needed to digitize and interpret symbols, text, and connections.
- Graph Neural Networks (GNNs) or Variational Autoencoders (VAEs): To represent and manipulate the circuit's netlist and structure in a machine-readable format, allowing for optimization and generation of new designs.
- Rule-Based Expert Systems: To enforce strict electrical engineering rules, standards compliance, and perform checks like Electrical Rule Checks (ERC) and design rule checks.
- Algorithms (e.g., Genetic Algorithms): For optimizing non-functional requirements such as cost, size, or power consumption, by searching through millions of potential circuit configurations
- CAD Software Compatibility: The model should export data in formats compatible with leading Electrical CAD (ECAD) software (e.g., Altium, Cadence, Mentor) for further PCB layout and manufacturing.
- Structured Output Formats: Generation of a complete Bill of Materials (BOM), netlists, and formal design reports (e.g., FMEA, power analysis, derating reports).
- Human-in-the-Loop Interface: A graphical user interface (GUI) for engineers to review, validate, and manually adjust the AI-generated schematics and resolve inconsistencies.
- Verification and Validation: The output must pass automated and human-expert validation to ensure technical accuracy and strategic alignment with project goals.
- Documentation and Cross-Referencing: Automatic generation of clear labels, annotations, and cross-references between schematic sheets for readability and maintenance.
Skill Sets Requirement:
- GenAI, Machine Learning , Applied Machine Learning, Machine Learning Operations, Computer Vision, Prompt Engineering
- Deep Learning , Reinforcement Learning, Supervised Learning , Artificial Neural Networks, PyTorch, Retrieval-Augmented Generation
- Big Data, AI Literacy, Programming in Python(Must and Proficient), R, SQL, Statistics , AI Tools, Analytical Thinking
Experiences: at least 2-3 years of experience.
