Research Engineer Jobs at Scale AI with Visa Sponsorship
Research Engineer roles at Scale AI sit at the intersection of machine learning infrastructure, data quality, and model evaluation. Scale AI actively sponsors visa holders across multiple categories for this function, making it a viable target for international candidates with strong technical backgrounds in AI research or applied ML.
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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.
See all 82+ Research Engineer at Scale AI jobs
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Get Access To All JobsTips for Finding Research Engineer Jobs at Scale AI Jobs
Align your research portfolio to Scale AI's work
Scale AI focuses on data labeling, RLHF pipelines, and model evaluation infrastructure. Frame your prior research around these areas in your CV and cover letter so reviewers can immediately map your work to their roadmap.
Confirm your OPT start date before applying
If you're on F-1 OPT, your employment start date must align with your EAD validity. Scale AI's hiring timelines can stretch across several interview rounds, so apply early enough to avoid a gap between offer acceptance and authorized start.
Target roles that specify ML systems or evaluation experience
Scale AI posts Research Engineer roles across distinct teams. Filtering for positions mentioning model benchmarking, annotation pipelines, or quality evaluation increases your odds of landing on a team with active sponsorship precedent for this function.
Use Migrate Mate to identify open Research Engineer roles at Scale AI
Filter by visa type and company to surface active Research Engineer listings at Scale AI that fit your authorization. Migrate Mate aggregates sponsoring employers so you're not manually sifting through postings that won't proceed with international candidates.
Prepare your LCA documentation before your H-1B filing window
Your employer must file a Labor Condition Application with the DOL before USCIS processes your H-1B petition. Confirm the prevailing wage level for Research Engineer roles in Scale AI's office location so you can flag any discrepancy before the petition is submitted.
Research Engineer at Scale AI jobs are hiring across the US. Find yours.
Find Research Engineer at Scale AI JobsFrequently Asked Questions
Does Scale AI sponsor H-1B visas for Research Engineers?
Yes, Scale AI sponsors H-1B visas for Research Engineer positions. The H-1B requires your role to qualify as a specialty occupation, which Research Engineer roles typically satisfy given their degree requirements in computer science, machine learning, or a related field. Keep the annual H-1B lottery cap in mind when planning your timeline, as selection is not guaranteed in any given cycle.
How do I apply for Research Engineer jobs at Scale AI?
Applications go through Scale AI's careers portal. Research Engineer roles at Scale AI typically involve multiple technical rounds covering ML fundamentals, systems design, and domain-specific evaluation tasks. Tailoring your application to highlight experience with model training pipelines, data quality, or RLHF gives your submission the clearest signal. You can browse open Research Engineer roles at Scale AI filtered by visa type on Migrate Mate.
Which visa types does Scale AI commonly sponsor for Research Engineers?
Scale AI sponsors H-1B, E-3, TN, F-1 OPT, F-1 CPT, J-1, and Green Card pathways including EB-2 and EB-3 for Research Engineers. H-1B is the most common route for candidates already in the U.S. without another status. Australian nationals can pursue the E-3, and Canadian or Mexican nationals in qualifying occupations may be eligible for the TN visa.
What qualifications does Scale AI expect for Research Engineer roles?
Scale AI's Research Engineer postings typically require a bachelor's or master's degree in computer science, statistics, or a closely related field, with hands-on experience in machine learning research or applied ML systems. Familiarity with model evaluation methods, large-scale data pipelines, or reinforcement learning from human feedback is a strong differentiator. Publications or open-source contributions in relevant areas can strengthen a borderline application.
How do I plan my timeline for a Research Engineer role at Scale AI if I need sponsorship?
H-1B petitions must be filed by April 1 for an October 1 start date, so back-plan your offer and onboarding accordingly. If you're on F-1 OPT, confirm your EAD expiration against Scale AI's expected start date before accepting an offer. For E-3 or TN applicants, consular processing or port-of-entry admission can move faster, but your employer still needs to complete the LCA with the DOL before USCIS or consular review begins.
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