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Research Scientist, Safety Post Training

Scale AISan Francisco, CA; New York, NYResearch
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Salary
Not listed
Job type
Full-time
Posted
18 May 2026
Status
Open · checked 7d ago

About this role

Scale AI is hiring a Research Scientist for Safety Post Training based in San Francisco, California or New York, New York to advance frontier AI system safety and alignment. This role is well-suited for machine learning experts eager to bridge the gap between technical research and global AI policy standards.

Role Overview

Scale AI operates Scale Labs, a dedicated initiative focused on policy research, agent robustness, and AI risk evaluation. As a Research Scientist specializing in Safety Post Training, the chosen professional will investigate and mitigate AI safety issues. The responsibilities center on building frameworks that help industry leaders, public sector groups, and governments comprehend complex AI behaviors and risks.

Key Responsibilities

Design and execute post-training pipelines to examine how different training choices impact model safety, alignment, and robustness.
Build interpretability-informed evaluations to uncover why models trigger undesirable, deceptive, or unsafe actions, and apply targeted mitigations.
Partner with cross-functional engineers, researchers, and policymakers to translate technical findings into practical benchmarks, safety standards, and best practices.

Requirements

Dedication to promoting safe, secure, and trustworthy deployments for frontier artificial intelligence technologies.
Hands-on background with reinforcement learning and post-training methods, including DPO, RLHF, GRPO, and related techniques.
A documented history of published machine learning research, with a strong focus on generative AI.
A minimum of three years of professional experience tackling sophisticated machine learning challenges in product development or research environments.
Excellent verbal and written communication abilities for collaborating across multidisciplinary teams.

Nice to Have

Practical exposure to mechanistic interpretability, probing, or other methodologies designed to inspect model internals.
Background in adversarial evaluation or red-teaming for post-trained models.
Familiarity with analyzing failure modes caused or masked by post-training, such as alignment faking, sycophancy, or reward hacking.

Skills and Tools

Reinforcement learning from human feedback (RLHF)
Direct preference optimization (DPO)
Group relative policy optimization (GRPO)
Post-training pipelines and machine learning debugging
Interpretability techniques and evaluation benchmark design

Salary and Benefits

The base salary range for this full-time position located in San Francisco, New York, or Seattle is $216,000 to $270,000 USD. Actual compensation depends on work location, job-related skills, qualifications, interview performance, and experience. Eligible roles also receive equity-based compensation subject to Board approval. Comprehensive benefits include medical, dental, and vision coverage, retirement plans, learning and development stipends, commuter stipends, and generous paid time off.

About the Company

Scale provides high-quality data and comprehensive full-stack technologies that enable top enterprises and governments to build, deploy, and oversee impactful AI applications. The organization partners closely with prominent industry leaders, academic institutions, and public sector agencies such as the U.S. Army and Air Force, Meta, and the Mayo Clinic. Dedicated to an inclusive workplace culture, the enterprise maintains equal opportunity employment practices.

How to Apply

Interested candidates should submit their application directly through the official Scale AI careers page to be considered for the position.

Questions candidates ask

What locations are eligible for this position?

This role is based in San Francisco, CA or New York, NY, with the listed base salary range also applying to Seattle.

What is the salary range for the Research Scientist role?

The base salary range for this full-time position is $216,000 to $270,000 USD, with additional equity and benefits available for eligible hires.

What experience is required to apply?

Applicants must have at least three years of experience solving complex machine learning challenges, a background in post-training and RL techniques, and a publication track record in machine learning.

What does the interview process look like?

Interviews evaluate practical machine learning prototyping and debugging skills, research concept understanding, and cultural alignment without using LeetCode-style coding tests.

What benefits are included with the job?

Eligible employees receive comprehensive health, dental, and vision coverage, retirement benefits, learning and development stipends, commuter stipends, and generous PTO.

Ready to apply?

The application is on the official Scale AI careers page.

Apply on company site