AI Research Engineer Jobs for OPT Students
AI Research Engineer roles sit at the intersection of machine learning research and production systems, making them one of the most competitive OPT job categories. Most positions require a master's or PhD and fall squarely within STEM OPT, giving you up to 36 months of work authorization to establish yourself in U.S. research teams.
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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.
How to Get Visa Sponsorship as an AI Research Engineer
Lead with publications and research output
AI Research Engineer hiring managers review your publication record before your resume. List arXiv preprints, conference papers, and workshop contributions prominently. Even one accepted NeurIPS or ICML paper substantially separates you from candidates without published work.
Target STEM-designated roles explicitly
Confirm the role is classified under a STEM CIP code before applying. AI Research Engineer positions typically fall under Computer Science or Electrical Engineering codes, which qualify for the 24-month STEM OPT extension beyond your initial 12 months.
Highlight your E-Verify employer requirement early
STEM OPT extension requires your employer to be E-Verify enrolled. Raise this in early conversations to avoid investing weeks in an interview process with an employer who cannot legally support your extension.
Showcase production-ready research skills
Many labs distinguish researchers who only prototype from those who can deploy. Demonstrate PyTorch or JAX proficiency alongside systems experience. Candidates who bridge research and engineering compress the sponsorship risk employers perceive during OPT periods.
Build a public portfolio of reproducible work
Open-source implementations of your research, well-documented GitHub repositories, and Hugging Face model cards all serve as persistent proof of skill. Hiring teams at research-focused employers frequently review these before extending interview invitations to OPT candidates.
Apply before your OPT start date when possible
Research roles have long hiring cycles, often eight to twelve weeks from first contact to offer. Starting your search three to four months before authorization begins gives employers the runway they need to complete approvals before your start date.
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Get Access To All JobsFrequently Asked Questions
Do AI Research Engineer roles qualify for the STEM OPT extension?
Yes, in most cases. AI Research Engineer positions are typically classified under Computer Science or Electrical Engineering CIP codes, both of which qualify for the 24-month STEM OPT extension. You should confirm the specific CIP code on your I-20 matches a STEM-designated field and verify that the employer is E-Verify enrolled before accepting an offer.
How do employers typically view OPT candidates for research engineering roles?
Research-focused employers, including university labs, AI startups, and large technology companies, are generally more comfortable hiring OPT candidates than employers in other industries because they already manage visa sponsorship for international researchers regularly. Your research output, technical depth, and alignment with the team's focus area matter more than your visa status in most screening conversations.
Where can I find AI Research Engineer jobs that are open to OPT candidates?
Migrate Mate filters job listings specifically for visa-sponsored and OPT-friendly roles, so you're not sifting through postings from employers who won't support work authorization. Browsing AI Research Engineer listings on Migrate Mate surfaces positions where sponsorship is already confirmed, which saves significant time during a job search with tight authorization deadlines.
Can I work as an AI Research Engineer on post-completion OPT before my STEM extension is approved?
Yes. You can begin working as soon as your OPT EAD card is valid and your employment is in a role directly related to your degree. You apply for the STEM extension up to 90 days before your initial OPT expires, and USCIS provides a 180-day automatic extension while the application is pending, so your authorization remains continuous.
What does the mandatory training plan requirement mean for AI Research Engineer roles?
During the STEM OPT extension, your employer must complete Form I-983, which outlines how the role provides practical training connected to your degree. For AI Research Engineer positions this is usually straightforward since the work directly involves applying advanced machine learning and computer science skills. Your employer's designated representative signs the plan and is responsible for reporting any material changes to your DSO.
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