AI Researcher Jobs at Scale AI with Visa Sponsorship
AI Researcher jobs at Scale AI focus on advancing 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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INTRODUCTION
As a Software Engineer on the ML Infrastructure team, you will design and build platforms for scalable, reliable, and efficient serving of LLMs. Our platform powers cutting-edge research and production systems, supporting both internal and external use cases across various environments. The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging research and engineering to deliver seamless experiences to our customers and accelerate innovation across the company.
ROLE AND RESPONSIBILITIES
You will:
- Build and maintain fault-tolerant, high-performance systems for serving LLMs workloads at scale.
- Build an internal platform to empower LLM capability discovery.
- Collaborate with researchers and engineers to integrate and optimize models for production and research use cases.
- Conduct architecture and design reviews to uphold best practices in system design and scalability.
- Develop monitoring and observability solutions to ensure system health and performance.
- Lead projects end-to-end, from requirements gathering to implementation, in a cross-functional environment.
BASIC QUALIFICATIONS
Ideally you'd have:
- 5+ years of experience building large-scale, high-performance backend systems.
- Strong programming skills in one or more languages (e.g., Python, Go, Rust, C++).
- Experience with LLM serving and routing fundamentals (e.g. rate limiting, token streaming, load balancing, budgets, etc.).
- Experience with LLM capabilities and concepts such as reasoning, tool calling, prompt templates, etc.
- Experience with containers and orchestration tools (e.g., Docker, Kubernetes).
- Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform).
- Proven ability to solve complex problems and work independently in fast-moving environments.
PREFERRED QUALIFICATIONS
Nice to haves:
- Experience with modern LLM serving frameworks such as vLLM, SGLang, TensorRT-LLM, or text-generation-inference.
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: $216,200—$270,250 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.
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Get Access To All JobsTips for Finding AI Researcher Jobs at Scale AI
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.
Verify your OPT start date before applying
F-1 OPT gives you 12 months of work authorization, extendable to 36 months with STEM OPT. If your OPT window starts late in the year, time your application so Scale AI can file your H-1B petition before April 1.
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.
Frequently 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 visa, TN visa, F-1 OPT, F-1 CPT, J-1 visa, 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 visa is available for Australian citizens. TN visa 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.