Research Engineer, Domain Scaling

Job Title

Research Engineer, Domain Scaling

Role Summary

The Research Engineer on the Domain Scaling team designs and implements data and training environments to improve Normal’s LLM-based agents for chip engineering, EDA, and related technical domains.

You will own end-to-end RL environment and data strategy work: identifying high-value tasks, designing rewards, sourcing and curating data, managing vendor relationships, and measuring impact on model capabilities.

Experience Level

Mid-level. No explicit years-of-experience requirement provided.

Responsibilities

Primary responsibilities include:

• Define and execute the data strategy for domain-specific knowledge work from task sourcing through RL training.
• Design RL environments and reward signals for high-value chip-engineering and EDA tasks.
• Manage relationships with external vendors: outreach, data-quality evaluation, and iterative reward design.
• Collaborate with domain experts to design data pipelines, evaluations, and QA frameworks.
• Develop QA and monitoring to detect reward hacking and ensure environment integrity.
• Run generalization and ablation experiments to measure how data and environment changes affect model performance.
• Work with AI researchers and product teams to translate capability goals into training environments, evaluations, and product features.

Requirements

Must-have:

• Experience applying post-training techniques to large language models for domain-specific or real-world use cases.
• Experience with reinforcement learning, reward design, or training-data curation for LLMs.
• Proven ability to manage technical vendor relationships and iterate quickly on feedback.
• Experience inspecting datasets and spotting data quality issues.
• Strong cross-functional collaboration and communication skills.
• Interest in applying AI to chip development and hardware-improvement workflows.

Nice-to-have:

• Experience training production ML systems.
• Experience designing evaluations or benchmarks for LLMs.
• Domain expertise in chip engineering, EDA, analog design, formal methods, or related verticals.
• Prior experience working with external technical partners or vendors on data or ML projects.

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.