ML Engineering Lead

Your Role in Our Mission: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. Knowledge of semiconductor design and manufacturing is a plus.The full job description covers all associated skills, previous experience, and any qualifications that applicants are expected to have.Responsibilities:Lead AI projects from concept to production deploymentSolve challenging AI and software engineering problems while promoting best practicesCreate showtime-ready benchmarks to continually measure quality and robustness of solutions relative to baselinesDevelop and deploy state-of-the-art AI models for problems in hardware engineering with complex logical and uncertainty-bound constraintsEvaluate state-of-the-art Bayesian and non-Bayesian approaches to reliable deep learning and formal verification of AI systemsSet up experimentation tools and synthetic data infrastructure to support rapid experimentation and iteration, with a clear path to production deploymentDevelop 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 generationWhat Makes You A Great Fit:4+ years of experience with deep learning frameworks like Pytorch, Tensorflow, JaxRich leadership experience over the "full stack" when it comes to designing, training, evaluating and deploying machine learning models, especially large generative modelsStrong software engineering skills, especially in building complex, distributed systems around AI technologiesExpertise in prompt engineering, fine-tuning, and deploying large generative models in production environmentsSkilled in handling and preprocessing large datasets for AI applications, including multimodal dataStrong understanding of AI evaluation metrics and benchmarking methodologiesExcellent communication skills, with the ability to explain complex AI concepts to technical and non-technical stakeholdersWhat Elevates Your Application:Experience deploying AI models in high-stakes or regulated environmentsHands-on experience with cloud platforms for large-scale AI deploymentFamiliarity with probabilistic programming languages (e.g., TensorFlow Probability, Pyro) and probabilistic reasoning methods (e.g. Bayesian NNs or Monte Carlo Tree Search)Specialized knowledge in advanced AI techniques such as few-shot learning, meta-learning, or AI alignment, and relevant frameworks like DSPyContributions to open-source AI projects or publications in top-tier AI conferences/journalsDeep curiosity for or experience in semiconductors and physicsA "defensive AI engineering" mindset, with experience handling the challenges of working with non-deterministic AI systems#J-18808-Ljbffr

Created: 2025-01-01