About the job
Normal Computing | Transformative Opportunities
At Normal Computing, we are at the forefront of innovation, developing the essential software and hardware that propel technology forward. Our contributions support the semiconductor industry and critical AI infrastructures, impacting the systems that power our everyday lives. Our collaborative team spans across dynamic cities including New York, San Francisco, Copenhagen, Seoul, and London.
Your Role in Our Vision:
We are in search of an AI Engineer to create production systems capable of interpreting extensive technical documents, such as chip design specifications, and transforming them into executable code. You will deliver tangible improvements to our customers on a weekly basis, while exploring the cutting-edge possibilities of AI in hardware through reinforcement learning, agentic coding, and superior software engineering practices.
Key Responsibilities:
- Oversee the entire AI development lifecycle from initial concept to production deployment and iterative enhancements.
- Develop and implement solutions powered by large language models (LLMs) to derive insights from intricate technical specifications.
- Navigate multi-modal complexities and investigate multi-agent and reinforcement learning methodologies for generating agentic code and utilizing tools effectively.
- Formulate strategies aimed at managing latency, output variance, and ensuring robust error handling at scale.
- Collaborate with product and engineering teams to seamlessly integrate AI functionalities into our platform.
- Mentor junior engineers and set best practices for AI development.
What Makes You Ideal for This Role:
- Demonstrable experience in deploying production-level AI systems involving language models, particularly those focused on document comprehension and agentic workflows.
- Strong software engineering background with experience in distributed systems and production-quality code.
- Proficient in Python and contemporary machine learning frameworks such as PyTorch, Hugging Face, and Transformers.
- Hands-on expertise in prompt engineering, fine-tuning, and deploying large language models.
- Aptitude for managing, cleaning, and preprocessing large-scale, diverse datasets.
- Familiarity with AI safety, bias mitigation, and ethical considerations.
- Ability to articulate complex AI concepts to both technical and non-technical audiences.
Bonus Qualifications:
- Experience with deploying AI systems in production settings, especially in the context of document understanding.
