aimlroles

Research Engineer, Domain Scaling

Normal Computing Corporation normalcomputing.com Open · verified Oct 21, 2026
Hybrid New York CopenhagenLondon +1 Full-time Mid-level AI Research

At a glance

Mid-level AI Research role at Normal Computing Corporation. New York · full-time · $200,000–$400,000 base.

SalaryStated by Normal Computing Corporation
$200,000 – $400,000
Base salary for this role, in USD per year, as published in the posting.
This role, from Normal Computing CorporationOur estimate for the market: $181,850–$300,000Median $237,500
The range includes the market median of $237,500 for mid-level AI research roles in New York.
Worked out from 32 postings that stated pay, median $237,500. Last updated Oct 18, 2026.
RoleAI Research
SeniorityMid-level
LocationNew York
WorkplaceHybrid
EmploymentFull-time
Base pay$200,000–$400,000
PostedAug 10, 2026 · 2mo ago
Also hiring inCopenhagen, London, Palo Alto
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Choose valuable domain tasks, source real or synthetic data, and carry that work through RL training
  • Find and assess data vendors, then shape reward signals using data-quality findings and feedback
  • Work with domain specialists to build data pipelines and evaluations for new capabilities
  • Create RL environments and quality checks that catch reward hacking and improve environment reliability
  • Run generalization tests and work with research and product teams to connect model gains to product features

What you bring

  • You have worked on post-training large language models for particular domains or practical use cases
  • You bring experience with reinforcement learning, reward design or curating training data for LLMs
  • You can manage technical vendor relationships and adjust quickly based on feedback
  • You are comfortable examining datasets closely to find quality problems

Who this fits

This mid-level research engineering role combines applied research with hands-on data work, and suits someone interested in improving AI capabilities for chip development. The position is hybrid in New York.

From the employer

Normal Computing | Build with Us

Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, Silicon Valley (Mountain View), London, Copenhagen, and Seoul.

The Role

The Domain Scaling team has the goal of making Normal’s Agents world-class at anything Chip-Engineering and EDA-related, UVM, debugging, analog, lean formalization, materials-aware optimization, etc. This is a unique role that combines executing directly on applied research and data sourcing (real-world and synthetic) to improve our models.

You'll own the end-to-end process of creating RL environments for new capabilities: identifying high-value tasks, designing reward signals, managing vendor relationships, and measuring impact on model performance.

What You Will Own

  • Own the data strategy for knowledge work verticals end-to-end, from task sourcing through RL training

  • Build and manage relationships with external vendors, including outreach, evaluation of data quality, and reward design

  • Collaborate with domain experts to design data pipelines and evaluations

  • Explore novel ways of creating RL environments for high-value tasks

  • Develop and improve QA frameworks to catch reward hacking and ensure environment quality

  • Run generalization experiments to measure how data strategy changes improve model capabilities

  • Partner with other AI researchers and product teams to translate capability goals into training environments, evals, and real product features

What Makes You a Great Fit

  • Have experience with post-training large language models for specific domains or real-world use cases

  • Have experience with reinforcement learning, reward design, or training data curation for LLMs

  • Are comfortable managing technical vendor relationships and iterating quickly on feedback

  • Find value in reading through datasets to understand them and spot issues

  • Have strong cross-functional collaboration skills

  • Are passionate about making AI more useful for chip development and recursive hardware self-improvement

  • Are excited about a role that includes a combination of applied research and hands-on data work

Bonus Points

  • Have experience training production ML systems

  • Have experience designing evals or benchmarks for LLMs

  • Have domain expertise in a vertical where we would like to make our models more useful

  • Have experience working with external vendors or technical partners

Equal Employment Opportunity Statement

Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.

Accessibility Accommodations

Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accommodations@normalcomputing.com.

Privacy Notice

By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Applicant Privacy Notice.