AI Researcher Jobs at Scale AI with Visa Sponsorship
Scale AI hires AI Researchers to advance data labeling infrastructure, model evaluation, and RLHF pipelines. The company sponsors a range of visa types for research roles, making it a realistic target for international candidates with backgrounds in machine learning, NLP, or human feedback systems.
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Get Access To All JobsINTRODUCTION
Scale AI is seeking a technically rigorous and driven AI Research Engineer to join our Enterprise Evaluations team. This high-impact role is critical to our mission of delivering the industry's leading GenAI Evaluation Suite. You will be a hands-on contributor to the core systems that ensure the safety, reliability, and continuous improvement of LLM-powered workflows and agents for the enterprise. The ideal candidate has a strong foundational knowledge of large language models, a passion for tackling complex evaluation challenges, and thrives in a dynamic, fast-paced research environment. We are looking for an engineer who can think outside the box, stays current with the latest literature in AI evaluation, and is passionate about integrating novel research ideas into our workflows to build best-in-class evaluation systems.
Responsibilities
- Partner with Scale’s Operations team and enterprise customers to translate ambiguity into structured evaluation data, guiding the creation and maintenance of gold-standard human-rated datasets and expert rubrics that anchor AI evaluation systems.
- Analyze feedback and collected data to identify patterns, refine evaluation frameworks, and establish iterative improvement loops that enhance the quality and relevance of human-curated assessments.
- Design, research, and develop LLM-as-a-Judge autorater frameworks and AI-assisted evaluation systems. This includes creating models that critique, grade, and explain agent outputs (e.g., RLAIF, model-judging-model setups), along with scalable evaluation pipelines and diagnostic tools.
- Pursue research initiatives that explore new methodologies for automatically analyzing, evaluating, and improving the behavior of enterprise agents, pushing the boundaries of how AI systems are assessed and optimized in real-world contexts.
BASIC QUALIFICATIONS
- Bachelor’s degree in Computer Science, Electrical Engineering, a related field, or equivalent practical experience.
- 2+ years of experience in Machine Learning or Applied Research, focused on applied ML systems or evaluation infrastructure.
- Hands-on experience with Large Language Models (LLMs) and Generative AI in professional or research environments.
- Strong understanding of frontier model evaluation methodologies and the current research landscape.
- Proficiency in Python and major ML frameworks (e.g., PyTorch, TensorFlow).
- Solid engineering and statistical analysis foundation, with experience developing data-driven methods for assessing model quality.
PREFERRED QUALIFICATIONS
- Advanced degree (Master’s or Ph.D.) in Computer Science, Machine Learning, or a related quantitative field.
- Published research in leading ML or AI conferences such as NeurIPS, ICML, ICLR, or KDD.
- Experience designing, building, or deploying LLM-as-a-Judge frameworks or other automated evaluation systems for complex models.
- Experience collaborating with operations or external teams to define high-quality human annotator guidelines.
- Expertise in ML research engineering, stochastic systems, observability, or LLM-powered applications for model evaluation and analysis.
- Experience contributing to scalable pipelines that automate the evaluation and monitoring of large-scale models and agents.
- Familiarity with distributed computing frameworks and modern cloud infrastructure.
COMPENSATION
- Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.
LOCATION
Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $179,400—$224,250 USD.
About us
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.
We comply with the United States Department of Labor's Pay Transparency provision.
PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
DATA PRIVACY
We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
INTRODUCTION
Scale AI is seeking a technically rigorous and driven AI Research Engineer to join our Enterprise Evaluations team. This high-impact role is critical to our mission of delivering the industry's leading GenAI Evaluation Suite. You will be a hands-on contributor to the core systems that ensure the safety, reliability, and continuous improvement of LLM-powered workflows and agents for the enterprise. The ideal candidate has a strong foundational knowledge of large language models, a passion for tackling complex evaluation challenges, and thrives in a dynamic, fast-paced research environment. We are looking for an engineer who can think outside the box, stays current with the latest literature in AI evaluation, and is passionate about integrating novel research ideas into our workflows to build best-in-class evaluation systems.
Responsibilities
- Partner with Scale’s Operations team and enterprise customers to translate ambiguity into structured evaluation data, guiding the creation and maintenance of gold-standard human-rated datasets and expert rubrics that anchor AI evaluation systems.
- Analyze feedback and collected data to identify patterns, refine evaluation frameworks, and establish iterative improvement loops that enhance the quality and relevance of human-curated assessments.
- Design, research, and develop LLM-as-a-Judge autorater frameworks and AI-assisted evaluation systems. This includes creating models that critique, grade, and explain agent outputs (e.g., RLAIF, model-judging-model setups), along with scalable evaluation pipelines and diagnostic tools.
- Pursue research initiatives that explore new methodologies for automatically analyzing, evaluating, and improving the behavior of enterprise agents, pushing the boundaries of how AI systems are assessed and optimized in real-world contexts.
BASIC QUALIFICATIONS
- Bachelor’s degree in Computer Science, Electrical Engineering, a related field, or equivalent practical experience.
- 2+ years of experience in Machine Learning or Applied Research, focused on applied ML systems or evaluation infrastructure.
- Hands-on experience with Large Language Models (LLMs) and Generative AI in professional or research environments.
- Strong understanding of frontier model evaluation methodologies and the current research landscape.
- Proficiency in Python and major ML frameworks (e.g., PyTorch, TensorFlow).
- Solid engineering and statistical analysis foundation, with experience developing data-driven methods for assessing model quality.
PREFERRED QUALIFICATIONS
- Advanced degree (Master’s or Ph.D.) in Computer Science, Machine Learning, or a related quantitative field.
- Published research in leading ML or AI conferences such as NeurIPS, ICML, ICLR, or KDD.
- Experience designing, building, or deploying LLM-as-a-Judge frameworks or other automated evaluation systems for complex models.
- Experience collaborating with operations or external teams to define high-quality human annotator guidelines.
- Expertise in ML research engineering, stochastic systems, observability, or LLM-powered applications for model evaluation and analysis.
- Experience contributing to scalable pipelines that automate the evaluation and monitoring of large-scale models and agents.
- Familiarity with distributed computing frameworks and modern cloud infrastructure.
COMPENSATION
- Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.
LOCATION
Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $179,400—$224,250 USD.
About us
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.
We comply with the United States Department of Labor's Pay Transparency provision.
PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
DATA PRIVACY
We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
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Get Access To All JobsTips for Finding AI Researcher Jobs at Scale AI Jobs
Frame your research around RLHF and evaluation
Scale AI's research function centers on reinforcement learning from human feedback and model quality evaluation. Candidates who position prior work around these areas, rather than generic ML research, land closer to the roles Scale is actively staffing.
Target Scale AI's RLHF and policy research teams
Scale AI organizes research across distinct product and policy verticals. Identifying which team is hiring for your specialization, whether that's frontier model evaluation or data quality research, helps you tailor your application and get in front of the right hiring manager.
Prepare a specialty occupation evidence packet early
For H-1B sponsorship, USCIS requires the role to qualify as a specialty occupation. Gather degree transcripts, publications, and a written role description from your recruiter before the offer stage so there are no delays when the employer files Form I-129.
Use Migrate Mate to filter AI Researcher openings at Scale AI
Scale AI posts research roles across multiple channels with inconsistent sponsorship language. Use Migrate Mate to surface verified AI Researcher openings at Scale AI filtered by your visa type, so you're applying to roles where sponsorship is already confirmed.
Clarify the LCA wage tier with your recruiter before signing
DOL Labor Condition Applications set prevailing wage levels that directly affect your offer. Ask your recruiter which wage tier the LCA is filed under for the specific research level you're being hired at, since Level I and Level II filings carry meaningfully different salary floors.
AI Researcher at Scale AI jobs are hiring across the US. Find yours.
Find AI Researcher at Scale AI JobsFrequently Asked Questions
Does Scale AI sponsor H-1B visas for AI Researchers?
Yes, Scale AI sponsors H-1B visas for AI Researcher roles. The company has a consistent track record of sponsoring research and engineering positions across visa categories. For H-1B sponsorship, your employer files Form I-129 with USCIS after the cap lottery selection, typically with an October 1 start date. If you're currently on F-1 OPT, you'll need to ensure your OPT remains valid through the lottery window.
Which visa types are commonly used for AI Researcher roles at Scale AI?
Scale AI sponsors H-1B, E-3, TN, F-1 OPT, F-1 CPT, J-1, and EB-2 or EB-3 Green Card pathways for research roles. F-1 OPT and CPT are common entry points for candidates finishing graduate programs. E-3 is available for Australian citizens. TN applies to Canadian and Mexican nationals in qualifying research classifications. H-1B is the primary long-term path for most international researchers.
What qualifications does Scale AI expect for AI Researcher positions?
Scale AI's AI Researcher roles typically require a graduate degree in machine learning, computer science, statistics, or a related field. Research experience with large language models, reinforcement learning from human feedback, or model evaluation is strongly weighted. Candidates with published work, particularly on alignment, data quality, or RLHF, tend to move further in the process. Practical experience with model fine-tuning or annotation pipelines is also valued.
How do I apply for AI Researcher jobs at Scale AI?
Applications go through Scale AI's careers page, but finding roles that confirm visa sponsorship upfront can be time-consuming. Migrate Mate aggregates verified AI Researcher openings at Scale AI with sponsorship details already filtered by visa type, so you can identify the right role before applying. When you apply, tailor your materials to Scale AI's research focus areas, specifically model evaluation, RLHF, and data quality.
How do I manage my visa timeline when interviewing at Scale AI?
The H-1B lottery opens in March for an October 1 start, so if your current status expires before then, you'll need bridging authorization. F-1 STEM OPT extensions give up to 36 months of work authorization and can bridge most timelines. If you receive an offer, confirm immediately whether Scale AI will file for premium processing, which USCIS adjudicates within 15 business days, to reduce uncertainty before your current authorization lapses.
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