Normal Computing is hiring a
AI Engineer Lead

Summary

The job is for an AI Engineer Lead at Normal Computing, a company specializing in AI for industrial applications. The role involves leading projects, mentoring team members, and driving cutting-edge machine learning applications across various aspects of the business. The ideal candidate has experience in leading AI engineering projects, strong software engineering skills, proficiency in Python, and expertise in large language models.

Requirements

• Proven experience in leading and managing AI engineering projects, particularly those involving large language models
• Strong software engineering skills, especially in building complex, distributed systems around AI technologies
• Proficiency in Python and experience with ML frameworks like PyTorch or TensorFlow
• Expertise in prompt engineering, fine-tuning, and deploying large language models in production environments
• Skilled in handling and preprocessing large datasets for AI applications, including multi-modal data
• Experience with AI safety considerations and best practices for responsible AI development
• 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

Responsibilities

• Lead projects from start to finish, ensuring timely and successful delivery
• Architect fault-tolerant systems around large language models and other AI technologies to process diverse data types
• Solve extremely tough software and AI engineering problems requiring novel, precise, and generalizable solutions
• Collaborate with cross-functional teams to integrate AI solutions into our products and services
• Mentor junior AI engineers, fostering a culture of growth and development in engineering best practices
• Develop and maintain robust evaluation frameworks and infrastructure to support rapid experimentation and iteration of AI models
• Design and implement strategies for handling the unique challenges of AI systems, such as high latency, variance, and potential errors

Preferred Qualifications

• Experience deploying AI models in high-stakes or regulated environments
• Hands-on experience with cloud platforms for large-scale AI deployment
• Specialized knowledge in advanced AI techniques such as few-shot learning, meta-learning, or AI alignment
• Contributions to open-source AI projects or publications in top-tier AI conferences/journals
• Proven ability to lead strategic AI initiatives and drive innovation in AI application development
• Experience balancing the creative exploration of AI capabilities with the need for robust, production-ready systems
• Proactive and adaptable mindset, thriving in a fast-paced environment where AI technologies rapidly evolve