CrawlJobs Logo
Scale Logo Scale · Research and Development

Research Scientist, Safety Post Training

United States, San Francisco, CA Employment contract 216000.00 - 270000.00 USD / Year · Job Posted May 29, 2026
Apply Position
Job Link Share

Job Description

As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision.

Job Responsibility

  • Develop and apply post-training methods and interpretability techniques to make frontier AI systems safer, and better understood by researchers and policymakers
  • Design and run post-training pipelines to study how training choices affect model safety, robustness, and alignment properties
  • Develop interpretability-informed evaluations that reveal how and why models produce unsafe, deceptive, or otherwise undesirable behaviors, and use those insights to guide targeted mitigations
  • Collaborate with policymakers, engineers, and other researchers to translate post-training and interpretability findings into actionable safety standards, evaluation benchmarks, and best practices

Requirements

  • Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches
  • A track record of published research in machine learning, particularly in generative AI
  • At least three years of experience addressing sophisticated ML problems, whether in a research setting or in product development
  • Strong written and verbal communication skills to operate in a cross-functional team

Nice to have

  • Experience with mechanistic interpretability, probing, or other techniques for understanding model internals
  • Familiarity with red-teaming or adversarial evaluation of post-trained models
  • Experience studying failure modes introduced or masked by post-training, such as reward hacking, sycophancy, or alignment faking

What we offer

  • comprehensive health, dental and vision coverage
  • retirement benefits
  • learning and development stipend
  • generous PTO
  • commuter stipend (eligible)
Scale - All Job Offers

Looking for more opportunities?

Search for other job offers that match your skills and interests.

Suggested Tags: Frontend Developer Secretary Talent Manager Salesforce Administrator Data Analyst
Similar Jobs for

Research Scientist, Safety Post Training

8 matching positions

Research Engineer, Post-Training

Meta is seeking Research Engineers to join the Post-Training team within Meta Su...
Location
Location
United States , Menlo Park
Salary
Salary:
257000.00 USD / Year ▼
meta.com Logo
Meta
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field
  • 5+ years of experience in machine learning engineering, machine learning research, or a related technical role
  • Proficiency in Python and experience with ML frameworks such as PyTorch
  • Experience identifying, designing, and completing medium to large technical features independently, without guidance
  • Demonstrated experiences in software engineering practices including version control, testing, and code review practices
  • Ability to work independently and adapt to rapidly changing priorities
Job Responsibility
Job Responsibility
  • Design, build, and scale full-stack data collection pipelines for post-training (SFT, RLHF) across text, vision, and action modalities
  • Develop and implement environments to capture complex agentic trajectories, including computer use agents, Deep research workflows, UI generation, and shopping agents
  • Collaborate with external data vendors and domain experts to source, securely ingest, and prepare high-quality datasets in fields like STEM, finance, legal, and health
  • Execute on the technical vision of research scientists to generate and filter high-quality synthetic data at scale
  • Build robust, reusable data processing pipelines that scale across multiple model lines and product areas
  • Contribute to tooling that measures and ensures the Quality, Diversity, and Safety of post-training datasets
What we offer
What we offer
  • bonus
  • equity
  • benefits
Read More
Arrow Right

Research Engineer, Post-Training

Meta is seeking Research Engineers to join the Post-Training team within Meta Su...
Location
Location
United States , Menlo Park
Salary
Salary:
217000.00 USD / Year ▼
meta.com Logo
Meta
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 3+ years of experience in machine learning engineering, machine learning research, or a related technical role
  • Proficiency in Python and experience with ML frameworks such as PyTorch
  • Experience identifying, designing, and completing medium to large technical features independently, without guidance
  • Software engineering practices including version control, testing, and code review practices
  • Ability to work independently and adapt to rapidly changing priorities
Job Responsibility
Job Responsibility
  • Design, build, and scale full-stack data collection pipelines for post-training (SFT, RLHF) across text, vision, and action modalities
  • Develop and implement environments to capture complex agentic trajectories, including computer use agents, research workflows, UI generation, and shopping agents
  • Collaborate with external data vendors and domain experts to source, securely ingest, and prepare high-quality datasets in fields like STEM, finance, legal, and health
  • Execute on the technical vision of research scientists to generate and filter high-quality synthetic data at scale
  • Build robust, reusable data processing pipelines that scale across multiple model lines and product areas
  • Contribute to tooling that measures and ensures the quality, variety, and safety of post-training datasets
What we offer
What we offer
  • bonus
  • equity
  • benefits
  • Fulltime
Read More
Arrow Right

Research Engineer, Post-Training

Meta is seeking Research Engineers to join the Post-Training team within Meta Su...
Location
Location
United States , Menlo Park
Salary
Salary:
181000.00 USD / Year ▼
meta.com Logo
Meta
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
  • Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field
  • 1+ years of experience in machine learning engineering, machine learning research, or a related technical role
  • Proficiency in Python and experience with ML frameworks such as PyTorch
  • Experience identifying, designing, and completing medium to large technical features independently, without guidance
  • Demonstrated experience in software engineering practices including version control, testing, and code review practices
  • Ability to work independently and adapt to rapidly changing priorities
Job Responsibility
Job Responsibility
  • Design, build, and scale full-stack data collection pipelines for post-training (SFT, RLHF) across text, vision, and action modalities
  • Develop and implement environments to capture complex agentic trajectories, including computer use agents, Deep research workflows, UI generation, and shopping agents
  • Collaborate with external data vendors and domain experts to source, securely ingest, and prepare high-quality datasets in fields like STEM, finance, legal, and health
  • Execute on the technical vision of research scientists to generate and filter high-quality synthetic data at scale
  • Build robust, reusable data processing pipelines that scale across multiple model lines and product areas
  • Contribute to tooling that measures and ensures the Quality, Diversity, and Safety of post-training datasets
What we offer
What we offer
  • bonus
  • equity
  • benefits
Read More
Arrow Right

Research Engineering Manager, Post-Training

Meta is seeking a Research Engineering Manager to lead the Post-Training team wi...
Location
Location
United States , Menlo Park
Salary
Salary:
219000.00 - 301000.00 USD / Year
meta.com Logo
Meta
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field
  • 4+ years of experience in machine learning engineering, machine learning research, or a related technical role
  • 3+ years of experience managing or leading technical teams, including hiring, mentoring, and performance management
  • Proficiency in Python and experience with ML frameworks such as PyTorch
  • Proven track record of leading medium to large-scale technical projects (specifically data pipelines or ML infrastructure) from conception to deployment
  • Software engineering practices including version control, testing, code review, and system design
  • Demonstrated ability to balance hands-on technical work with people management and strategic planning
  • Great communication skills with the ability to influence cross-functional stakeholders
Job Responsibility
Job Responsibility
  • Build, mentor, and grow a team of research engineers focused on full-stack post-training data infrastructure
  • Conduct performance reviews, career development conversations, and provide technical mentorship to team members
  • Foster a Culture of Engineering Excellence, data rigor, and rapid iteration within the team
  • Partner with recruiting to hire world-class research engineering talent
  • Oversee the development and scaling of data collection pipelines for high-value domains (STEM, GDP-valuable tasks, finance, legal, health) and complex agentic workflows (deep research, computer use, shopping agents)
  • Establish and manage partnerships with external data vendors to source and securely prepare expert-level post-training datasets
  • Influence the technical roadmap for data infrastructure in collaboration with the MSL Infra team
  • Translate the strategic vision of research scientists into actionable engineering plans for synthetic data generation, SFT, and RLHF pipelines
  • Partner with research scientists, product teams, and model training teams to align data collection priorities with organizational capability goals
  • Build robust, reusable data pipelines that can rapidly deliver high-quality datasets to multiple model lines
What we offer
What we offer
  • bonus
  • equity
  • benefits
  • Fulltime
Read More
Arrow Right

Research Scientist, Agent Robustness

As a Research Scientist working on Agent Robustness you will work on the fundame...
Location
Location
United States , San Francisco; New York
Salary
Salary:
197400.00 - 246750.00 USD / Year
scale.com Logo
Scale
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Commitment to mission of promoting safe, secure, and trustworthy AI deployments
  • Practical experience conducting technical research collaboratively
  • Experience building and leveraging agent scaffolding, designing evaluation harnesses, and quickly turning new ideas into working prototypes
  • Experience with post-training and RL techniques such as RLHF, DPO, GRPO
  • A track record of published research in machine learning, particularly in generative AI
  • At least three years of experience addressing sophisticated ML problems
  • Strong written and verbal communication skills
Job Responsibility
Job Responsibility
  • Research the science of AI agent capabilities with a focus on safety, risk factors, and benchmarking methodologies
  • Design and build harnesses to test AI agents’ tendency to take harmful actions
  • Design and build exploits and mitigations for new failure modes
  • Characterize and design mitigations for potential failure modes of systems involving multiple interacting AI agents
What we offer
What we offer
  • Comprehensive health, dental and vision coverage
  • Retirement benefits
  • Learning and development stipend
  • Generous PTO
  • Commuter stipend
  • Equity grant
  • Fulltime
Read More
Arrow Right

AI Research Scientist - Speech and Language

Reality Labs Research is Meta’s innovation engine for next-generation AR/VR, AI,...
Location
Location
United States , Redmond
Salary
Salary:
184000.00 - 257000.00 USD / Year
meta.com Logo
Meta
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Generative AI, or a relevant technical field
  • Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
  • Demonstrated programming skills in Python and familiarity with large-scale distributed training
  • Familiarity to learn new programming languages quickly
  • Can design, implement, and evaluate RL algorithms in production or research settings
  • Problem-solving, communication, and collaboration skills
Job Responsibility
Job Responsibility
  • Design, implement, and optimize LLM-based agents for a variety of applications, leveraging the latest advances in generative AI
  • Apply reinforcement learning algorithms to improve LLM performance, safety, and alignment
  • Integrate models and orchestrations in production
  • Collaborate with cross-functional teams (research, engineering, product) to deploy and evaluate LLM agents in real-world scenarios
  • Analyze and interpret experimental results, iterate on model architectures, and drive continuous improvement
  • Contribute to the broader AI/ML community at Meta through knowledge sharing, code reviews, and technical mentorship
  • Lead and contribute to research and development of post-training methods, including RLHF (Reinforcement Learning from Human Feedback), reward modeling, and other feedback-based approaches
  • Apply AI Models to Speech Encoding, Decoding, and Synthesis problems
  • Develop Natural Language interaction systems
What we offer
What we offer
  • bonus
  • equity
  • benefits
Read More
Arrow Right

Language Research Scientist

We are seeking a technically skilled GenAI scientist to join our team focused on...
Location
Location
Switzerland , Zurich
Salary
Salary:
Not provided
meta.com Logo
Meta
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Generative AI, or a relevant technical field
  • Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
  • Good programming skills in Python and familiarity with large-scale distributed training
  • Familiarity to learn new programming languages quickly
  • Can design, implement, and evaluate RL algorithms in production or research settings
  • Problem-solving, communication, and collaboration skills
Job Responsibility
Job Responsibility
  • Design, implement, and optimize LLM-based agents for a variety of applications, leveraging the latest advances in generative AI
  • Apply reinforcement learning algorithms to improve LLM performance, safety, and alignment
  • Integrate models and orchestrations in production
  • Collaborate with cross-functional teams (research, engineering, product) to deploy and evaluate LLM agents in real-world scenarios
  • Analyze and interpret experimental results, iterate on model architectures, and drive continuous improvement
  • Contribute to the broader AI/ML community at Meta through knowledge sharing, code reviews, and technical mentorship
  • Lead and contribute to research and development of post-training methods, including RLHF (Reinforcement Learning from Human Feedback), reward modeling, and other feedback-based approaches
Read More
Arrow Right

Distinguished Scientist

In this role, you will define and drive the technical vision for long-horizon, s...
Location
Location
United States
Salary
Salary:
270700.00 - 432300.00 USD / Year
Zillow
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • A PhD in Computer Science, Electrical Engineering, or a related field—or equivalent experience—with emphasis in areas such as foundational LLMs, agentic AI, reinforcement learning, AI planning, or natural language processing
  • 10+ years of hands-on experience building and deploying large-scale AI systems, including at least several years focused on agent-based systems, multi-agent collaboration, or long-horizon conversational assistants
  • Deep, current expertise in generative and agentic AI, including multimodal foundation models, transformers, advanced reasoning models, and post-training techniques (SFT, DPO, RLHF/RLAIF, preference learning, etc.)
  • A track record of leading ambiguous, cross-functional initiatives from concept to production—framing the problem, shaping data strategy, designing models and evaluation, and iterating based on live metrics and user feedback
  • Demonstrated impact in the research community through publications at top venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR) and/or widely used open-source contributions in LLMs, agentic frameworks, or related areas
  • Experience designing evaluation and supervision frameworks for long-horizon agents, ideally in regulated or high-stakes domains such as finance, healthcare, or large-scale marketplaces, with an emphasis on safety, fairness, and trust
  • Strong technical leadership skills: you mentor senior scientists and engineers, create clarity amid ambiguity, and build alignment across research, engineering, product, and leadership stakeholders
  • Excellent communication skills with the ability to distill complex ideas into clear narratives for executives, cross-functional partners, and external audiences
Job Responsibility
Job Responsibility
  • Own the end-to-end research and technical strategy for long-horizon agentic experiences across shopping, financing, and professional workflows, in close partnership with the Agentic AI, data platform, and product teams
  • Design and advance LLM post-training and evaluation methods (e.g., SFT, preference learning, RLHF/RLAIF, long-context modeling) tailored to supervised, high-stakes journeys in a complex, regulated domain
  • Architect systems that combine persistent memory, tool use, and multi-agent collaboration to deliver consistent, context-rich guidance over long timelines
  • Translate Zillow’s heterogeneous data (text, voice, behavioral, and structured real-estate/transaction data) into agent-ready knowledge and signals, in partnership with data and platform teams
  • Collaborate with product and design to define success metrics, evaluation frameworks, and experiment plans for agentic experiences, including human-in-the-loop supervision and safety reviews
  • Operate as a senior IC with the option to lead a small pod (up to ~5 scientists/engineers) focused on long-horizon agentic systems, mentoring principal-level talent and setting a high technical bar
  • Represent Zillow’s work externally through publications, talks, open-source contributions, and thoughtful engagement with the research community, helping position Zillow as a destination for top agentic AI talent
What we offer
What we offer
  • competitive base salary
  • eligibility for equity awards
  • Fulltime
Read More
Arrow Right