ML Engineer Jobs at Scale AI with Visa Sponsorship
Scale AI hires ML Engineers to build and evaluate the data pipelines that train frontier AI systems. The company sponsors a range of work visas for this function, making it a realistic target if you're on OPT, holding an H-1B, or coming from outside the U.S. on an E-3 or TN.
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Get Access To All JobsINTRODUCTION
Scale’s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you!
ROLE AND RESPONSIBILITIES
You will:
- Build, profile and optimize our training and inference framework
- Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation
- Research and integrate state-of-the-art technologies to optimize our ML system
BASIC QUALIFICATIONS
Ideally you’d have:
- Strong excitement about system optimization
- Experience with multi-node LLM training and inference
- Experience with developing large-scale distributed ML systems
- Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc.
- Strong written and verbal communication skills and the ability to operate in a cross functional team environment
PREFERRED QUALIFICATIONS
Nice to haves:
- Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.
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
For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $218,400—$273,000 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: 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’s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you!
ROLE AND RESPONSIBILITIES
You will:
- Build, profile and optimize our training and inference framework
- Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation
- Research and integrate state-of-the-art technologies to optimize our ML system
BASIC QUALIFICATIONS
Ideally you’d have:
- Strong excitement about system optimization
- Experience with multi-node LLM training and inference
- Experience with developing large-scale distributed ML systems
- Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc.
- Strong written and verbal communication skills and the ability to operate in a cross functional team environment
PREFERRED QUALIFICATIONS
Nice to haves:
- Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.
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
For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $218,400—$273,000 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: 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 ML Engineer Jobs at Scale AI Jobs
Frame your ML work around data quality
Scale AI's ML Engineer roles center on RLHF pipelines, model evaluation, and training data infrastructure, not pure research. Tailor your resume and portfolio to show hands-on work with data labeling systems, feedback loops, or model benchmarking before you apply.
Target Scale AI's applied ML teams specifically
Scale AI operates distinct tracks: research, infrastructure, and applied ML for enterprise clients. Job postings on their careers page often signal which track you're interviewing for. Applied ML and data engine roles tend to align more directly with sponsored positions and faster hiring cycles.
Understand the H-1B cap and Scale AI's filing window
Cap-subject H-1B petitions must be submitted in April for an October 1 start date. If you receive an offer outside that window, ask Scale AI's immigration team whether a cap-exempt pathway or a bridge on your current status can cover the gap.
Use Migrate Mate to filter verified ML Engineer openings
Sponsored ML Engineer roles at Scale AI aren't always flagged clearly on general job boards. Use Migrate Mate to browse openings filtered by visa type and employer sponsorship history so you're only spending time on roles where sponsorship is already confirmed.
Prepare your specialty occupation documentation before the offer
USCIS evaluates H-1B petitions partly on whether the role requires a specific bachelor's degree. For ML Engineer roles, gather transcripts, any graduate credentials, and project documentation that ties your specialized degree directly to the responsibilities in Scale AI's job description.
ML Engineer at Scale AI jobs are hiring across the US. Find yours.
Find ML Engineer at Scale AI JobsFrequently Asked Questions
Does Scale AI sponsor H-1B visas for ML Engineers?
Yes, Scale AI sponsors H-1B visas for ML Engineer roles. The H-1B is the most common path for international candidates in this function. Because H-1B cap registrations open in March and employment can't begin until October 1, timing matters. If you're already on an H-1B with another employer, a transfer can happen at any point in the year.
How do I apply for ML Engineer jobs at Scale AI?
Applications go through Scale AI's careers page, where roles are listed by team and function. ML Engineer positions often require a technical screen followed by a system design or ML evaluation exercise. Migrate Mate lets you browse confirmed ML Engineer openings at Scale AI filtered by visa type, so you can identify the right role before applying directly.
Which visa types does Scale AI commonly sponsor for ML Engineers?
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 ML Engineers. Australian citizens typically use the E-3, Canadian and Mexican nationals often use TN, and recent graduates commonly start on F-1 OPT while their employer files an H-1B petition during the annual cap registration window.
What qualifications does Scale AI expect for ML Engineer roles?
Most ML Engineer openings at Scale AI require a bachelor's or master's degree in computer science, machine learning, or a closely related field. Practical experience with model training pipelines, data annotation workflows, or RLHF systems carries significant weight. Roles on the applied side often prioritize demonstrated ability to ship production ML systems over pure research credentials.
How long does the visa sponsorship process take for an ML Engineer offer at Scale AI?
Timeline depends on visa type. H-1B cap cases follow a fixed cycle: registration in March, lottery results by April, and an October 1 start date. H-1B transfers for candidates already in status can close in weeks, especially with USCIS premium processing. E-3 and TN visas can move faster, often resolved at a consular appointment or port of entry within weeks of receiving an offer.
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