AI Engineer
Normal ComputingJob Title
AI Engineer
Role Summary
The AI Engineer will design, build, and deploy production AI systems that convert complex technical documents (for example, chip design specifications) into working code and tooling. The role spans model development, systems engineering, and close collaboration with product and platform teams.
Work will focus on document understanding, agentic code generation, reinforcement learning, and production-quality deployment and monitoring across Normal's engineering sites.
Experience Level
Mid-level (Level - Mid-Career). Years of experience: Not specified.
Responsibilities
Primary responsibilities include:
- Lead end-to-end AI development from concept through production deployment and iteration.
- Design and implement LLM-based document understanding systems to extract structured meaning from complex technical specifications.
- Research and build agentic systems, including multi-agent workflows and RL approaches for code generation and tool use.
- Engineer production-quality solutions that manage latency, reduce output variance, and handle errors gracefully at scale.
- Integrate AI capabilities into the platform in collaboration with product and engineering teams.
- Mentor junior engineers and establish best practices for AI development and deployment.
Requirements
Must-have qualifications:
- Experience delivering production AI systems using language models, preferably involving document understanding or agentic workflows.
- Strong software engineering skills and experience with distributed systems and production-grade code.
- Proficiency in Python and modern ML frameworks (PyTorch, Hugging Face, transformers).
- Hands-on experience with prompt engineering, fine-tuning, and deploying large language models.
- Experience cleaning, preprocessing, and managing large, heterogeneous datasets.
- Ability to explain complex AI concepts to both technical and non-technical stakeholders.
Nice-to-have:
- Experience with hardware design, hardware verification, or EDA tooling.
- Experience deploying AI systems in mission-critical or high-stakes production environments.
- Familiarity with cloud platforms for large-scale AI infrastructure (AWS, GCP, Azure).
- Research or applied experience with LLM agents, RL (offline/online, RLHF/RLAIF), constrained decoding, or program synthesis.
- Open-source contributions or publications in AI/ML venues.
Education Requirements
Not specified.
About the Company
Company: Normal Computing
Headquarters: New York, NY, USA
Normal Computing develops software and hardware solutions for the semiconductor and AI infrastructure industries, specializing in ASICs for image and video diffusion inference and AI accelerators. The company focuses on architecture and microarchitecture of compute blocks, PE array design, ISA co-design, and FPGA prototyping.
