Machine Learning Scientist Jobs at Scale AI with Visa Sponsorship
Machine Learning Scientist roles at Scale AI sit at the intersection of research and applied AI, typically requiring deep expertise in model development, data pipelines, and evaluation frameworks. Scale AI has a consistent track record of sponsoring international talent across multiple visa categories for technical roles like this one.
See All Machine Learning Scientist at Scale AI JobsOverview
Showing 5 of 43+ Machine Learning Scientist Jobs at Scale AI jobs
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
See all 43+ Machine Learning Scientist Jobs at Scale AI
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Scientist Jobs at Scale AI.
Get Access To All JobsAbout Scale
At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations.
About The ACE Team
The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more.
About This Role
This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions.
BASIC QUALIFICATIONS
- Practical experience working with LLMs, with proficiency in frameworks like Pytorch, Jax, or Tensorflow. You should also be adept at interpreting research literature and quickly turning new ideas into prototypes.
- A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.)
- At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.
- Strong written and verbal communication skills and the ability to operate cross-functionally.
PREFERRED QUALIFICATIONS
- Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax.
- Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents.
- Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.
- Familiarity with agentic reasoning methods such as STaR and PLANSEARCH
- Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.
Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions.
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.
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: $259,200—$324,000 USD.
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.
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.
About Scale
At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations.
About The ACE Team
The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more.
About This Role
This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions.
BASIC QUALIFICATIONS
- Practical experience working with LLMs, with proficiency in frameworks like Pytorch, Jax, or Tensorflow. You should also be adept at interpreting research literature and quickly turning new ideas into prototypes.
- A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.)
- At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.
- Strong written and verbal communication skills and the ability to operate cross-functionally.
PREFERRED QUALIFICATIONS
- Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax.
- Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents.
- Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.
- Familiarity with agentic reasoning methods such as STaR and PLANSEARCH
- Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.
Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions.
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.
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: $259,200—$324,000 USD.
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.
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.
See all 43+ Machine Learning Scientist at Scale AI jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Scientist at Scale AI roles.
Get Access To All JobsTips for Finding Machine Learning Scientist Jobs at Scale AI Jobs
Align your research background to Scale AI's evaluation work
Scale AI's ML Scientist roles often focus on model evaluation, RLHF, and data quality research. Framing your experience around these areas, rather than general ML research, signals fit to their technical hiring teams before the first screen.
Prepare your credential equivalency documentation early
If you hold a three-year bachelor's degree or a degree from a non-U.S. institution, get a credential evaluation from a NACES-approved service before interviews start. Delays at this stage can slow H-1B petition timelines significantly.
Confirm sponsorship scope during the offer stage
Ask the recruiter specifically which visa categories the offer covers and whether they file for both cap-subject H-1B and cap-exempt alternatives. Scale AI sponsors multiple visa types, so clarifying this upfront prevents surprises after you've accepted.
Use Migrate Mate to identify open Machine Learning Scientist roles at Scale AI
Filter by visa type on Migrate Mate to surface Scale AI listings that match your authorization status, whether you're on F-1 OPT, H-1B, or another category, so you apply to roles where sponsorship is already confirmed.
Track the H-1B registration window and plan your start date
USCIS opens H-1B registration in March each year for an October 1 start date. If you're targeting a full-time Machine Learning Scientist role, coordinate your offer timing so your employer can file in the same registration cycle.
Document your specialized skills for the specialty occupation determination
For H-1B petitions, DOL and USCIS require evidence that the role requires a specific, specialized degree. Collect publications, project documentation, or employer letters that demonstrate your ML work required advanced, field-specific expertise rather than general engineering skills.
Machine Learning Scientist at Scale AI jobs are hiring across the US. Find yours.
Find Machine Learning Scientist at Scale AI JobsFrequently Asked Questions
Does Scale AI sponsor H-1B visas for Machine Learning Scientists?
Yes, Scale AI sponsors H-1B visas for Machine Learning Scientist roles. The company participates in the annual H-1B registration process, which opens each March through USCIS for an October 1 start date. If you're already in H-1B status with another employer, Scale AI can also file an H-1B transfer, which lets you start work as soon as USCIS receives the petition.
Which visa types does Scale AI commonly sponsor for Machine Learning Scientist roles?
Scale AI sponsors several visa categories for this role, including H-1B, E-3 (for Australian citizens), TN (for Canadian and Mexican nationals), and Green Card pathways such as EB-2 and EB-3. The company also supports F-1 OPT and CPT for students, and J-1 for qualifying exchange visitors. Which category applies depends on your citizenship and current immigration status.
What qualifications does Scale AI expect for Machine Learning Scientist positions?
Scale AI typically hires Machine Learning Scientists with a graduate degree in computer science, statistics, or a closely related field, along with hands-on experience in model training, evaluation pipelines, or applied research. Familiarity with reinforcement learning from human feedback, large language model evaluation, or data quality research is particularly relevant given Scale AI's core product focus.
How do I apply for Machine Learning Scientist jobs at Scale AI?
You can browse and apply for Machine Learning Scientist roles at Scale AI through Migrate Mate, which filters openings by visa sponsorship type so you can confirm eligibility before applying. When you apply, tailor your materials to highlight experience with model evaluation, data pipelines, or applied AI research. Scale AI's interview process typically includes technical screens, coding assessments, and research presentations.
How do I time my application if I'm on F-1 OPT and want long-term sponsorship at Scale AI?
If you're on F-1 OPT, you have up to 12 months of work authorization after graduation, with a possible 24-month STEM OPT extension for qualifying degrees. To convert to H-1B, your employer must register you in the March lottery for an October 1 start. Starting your job search at Scale AI at least six months before your OPT expires gives you enough runway to go through their hiring process and get registered in time.
See which Machine Learning Scientist at Scale AI employers are hiring and sponsoring visas right now.
Search Machine Learning Scientist at Scale AI Jobs