AI Engineer

About the Role

Mirabilis Design Incorporation is seeking a talented AI Engineer with expertise in Large Language Models (LLMs) and Applied AI for our engineering software domain. This role involves defining the future of AI within our organization, both for internal processes and customer-facing features.

Key Responsibilities

• Develop and articulate a strategic roadmap for AI capabilities, aligning with business objectives for internal tools and customer features.
• Conduct experiments and analysis using existing VisualSim models and datasets.
• Evaluate AI-generated outputs against expected and validated results to ensure accuracy and performance.
• Identify and meticulously define requirements for training data.
• Collaborate closely with engineering teams to generate, clean, and label datasets effectively.
• Design, build, and fine-tune LLM-based solutions tailored for specific engineering use cases.
• Architect and implement large-scale test scenarios to rigorously validate the correctness and reliability of AI models.

Example AI Use Cases

• Leverage VisualSim XML models for AI-driven insights.
• Analyze workloads, configurations, and expected results to optimize engineering processes.
• Utilize AI to auto-generate test cases and validation scenarios, streamlining quality assurance.
• Develop AI tools for generating documentation and model explanations, enhancing knowledge transfer.
• Create AI-powered tools designed to significantly reduce manual engineering effort.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a closely related field.
• 2-3 years of relevant professional experience, such as an AI/ML Engineer, or substantial project work as a Research/Applied AI Intern.
• Strong foundation in statistics and probability.
• Hands-on proficiency with:
  • Python for AI development.
  • Major ML / AI frameworks including PyTorch, TensorFlow, and HuggingFace.
  • Working knowledge of LLMs, prompt engineering, and model fine-tuning techniques.

Nice to Have

• Prior experience working with structured or semi-structured data like XML, JSON, and log files.
• Exposure to engineering, simulation, or Electronic Design Automation (EDA) tools.
• Proven ability in validating AI outputs against deterministic or expected results.
• Demonstrated ability to work independently and conceptualize/design experiments from start to finish.