ML Engineering Lead, Normal Computing

• Knowledge of semiconductor design and manufacturing is a plus
• 4+ years of experience with deep learning frameworks like Pytorch, Tensorflow, Jax
• Rich leadership experience over the “full stack” when it comes to designing, training, evaluating and deploying machine learning models, especially large generative models
• Strong software engineering skills, especially in building complex, distributed systems around AI technologies
• Expertise in prompt engineering, fine-tuning, and deploying large generative models in production environments
• Skilled in handling and preprocessing large datasets for AI applications, including multimodal data
• Strong understanding of AI evaluation metrics and benchmarking methodologies
• Excellent communication skills, with the ability to explain complex AI concepts to technical and non-technical stakeholders

Desirable

• As an AI Engineer Lead, you will play a pivotal role in leading and managing projects from concept to production, mentoring team members, and influencing the strategic direction of our AI initiatives
• Lead AI projects from concept to production deployment
• Solve challenging AI and software engineering problems while promoting best practices
• Create showtime-ready benchmarks to continually measure quality and robustness of solutions relative to baselines
• Develop and deploy state-of-the-art AI models for problems in hardware engineering with complex logical and uncertainty-bound constraints
• Evaluate state-of-the-art Bayesian and non-Bayesian approaches to reliable deep learning and formal verification of AI systems
• Set up experimentation tools and synthetic data infrastructure to support rapid experimentation and iteration, with a clear path to production deployment
• Develop strategies to manage AI-specific challenges (latency, variance, errors)
• Keep up with AI advancements, especially in language models and multi-modal AI, and synthetic data generation