Remote AI Evaluation & Alignment Research Engineer

United States Digital Space LLC; United States; Remote; USD 120,000 - 160,000; Full time

Benefits offered by this job

External Handbook

Website

Youtube

Job summary

United States Digital Space LLC seeks an AI Research Engineer to advance evaluation methodologies, alignment techniques, and synthetic data generation. You will bridge cutting-edge research with practical applications and contribute to publications and open-source projects.

Collaborating with ML engineers, data scientists, and product teams, you will design scalable experiments, build evaluation frameworks for LLMs, and develop tooling to translate research into products.

Qualifications

• 5+ years of engineering experience with significant AI/ML focus.
• Demonstrated research experience through publications, open-source contributions, or impactful projects.
• Strong engineering fundamentals and experience implementing AI systems in production environments.
• Deep knowledge of LLM evaluation methodologies, alignment techniques, and model optimization approaches.
• Excellent communication skills and ability to explain complex research concepts clearly.

Responsibilities

• Lead independent research projects in AI evaluation methodologies, alignment techniques, and synthetic data generation.
• Design and implement novel evaluation frameworks for LLMs and agent systems grounded in human data.
• Contribute to the academic AI community through publications and open-source contributions.
• Stay at the forefront of AI research and pioneer approaches to tackling open challenges.
• Work with ML engineers, data scientists, and product teams to translate research into practical applications.

Skills

AI/ML engineering

Publications/Open-source

LLM evaluation

Model optimization

Strong communication

Job description

United States Digital Space LLC seeks an AI Research Engineer to advance evaluation methodologies, alignment techniques, and synthetic data generation. You will bridge cutting-edge research with practical applications and contribute to publications and open-source projects.

Collaborating with ML engineers, data scientists, and product teams, you will design scalable experiments, build evaluation frameworks for LLMs, and develop tooling to translate research into products.