Poolside Visa Sponsorship USA
Poolside is an AI research company building foundation models for code generation, attracting technical talent from around the world. The company has begun sponsoring H-1B visas, making it a emerging option for international software engineers and AI researchers seeking sponsorship in the U.S.
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Get Access To All JobsAbout Poolside
In this decade, the world will create Artificial General Intelligence. There will only be a small number of companies who will achieve this. Their ability to stack advantages and pull ahead will define the winners. These companies will move faster than anyone else. They will attract the world's most capable talent. They will be on the forefront of applied research, engineering, infrastructure and deployment at scale. They will continue to scale their training to larger & more capable models. They will be given the right to raise large amounts of capital along their journey to enable this. They will create powerful economic engines. They will obsess over the success of their users and customers. Poolside exists to be this company - to build a world where AI will be the engine behind economically valuable work and scientific progress.
About Our Team
We are a remote-first team that sits across Europe and North America. We come together once a month in-person for 3 days, always Monday-Wednesday, with an open invitation to stay the whole week. We also do longer off-sites once a year. Our team is a combination of more research and more engineering-oriented profiles, however, everyone deeply cares about the quality of the systems we build and has a strong underlying knowledge of software development. We believe that good engineering leads to faster development iterations, which allows us to compound our efforts.
About The Role
You’ll be working on our data team focused on the quality of the datasets being delivered for training our models. This is a hands-on role where your #1 mission would be to improve the quality of the pretraining datasets by leveraging your previous experience, intuition and training experiments. This role particularly focuses on generating synthetic data at scale and determining the best strategies to leverage such data into training large models. You’ll closely collaborate with other teams like Pretraining, Posttraining, Evals, and Product to define high-quality data needs that map to missing model capabilities and downstream use cases. Staying in sync with the latest research in synthetic data generation and pretraining is key to success in this role. You will constantly lead original research initiatives through short, time-bounded experiments while deploying highly technical engineering solutions into production. With the volumes of data to process being massive, you'll have a performant distributed data pipeline together with a large GPU cluster at your disposal.
YOUR MISSION
To deliver large, high-quality, and diverse synthetic datasets mixing natural language and code modalities to train best-in-class coding agents.
Responsibilities
- Follow the latest research related to LLMs and synthetic data generation in particular. Be familiar with the most relevant open-source datasets and models.
- Design and implement complex pipelines that can generate large amounts of data while maintaining high diversity and optimizing the resources available.
- Closely work with other teams such as Pretraining, Posttraining, Evals and Product to ensure alignment on the quality of the models delivered.
- Continuously measure and refine the quality of the datasets being generated while validating the final data strategy through quantitative data ablation experiments.
Skills & Experience
- Strong machine learning and engineering background
- Experience with Large Language Models (LLM), including:
+ Understanding of how LLMs learn
+ Data ablations and scaling laws
+ Post-training techniques
+ Training reasoning and agentic models
- Experience with implementing cost-efficient, complex pipelines to generate synthetical datasets at scale optimizing for data quality, correctness, diversity, etc.
- Experience with evals tracking model capabilities (general knowledge, reasoning, math, coding, long-context, etc)
- Experience in building trillion-scale pretraining datasets, and familiarity with concepts like data curation, deduplication, data mixing, tokenization, curriculum, impact of data repetition, etc.
- Excellent programming skills in Python
- Strong prompt engineering skills
- Experience working with large-scale GPU clusters and distributed data pipelines
- Strong obsession with data quality
- Research experience:
+ Author of scientific papers on any of the topics: applied deep learning, LLMs, source code generation, etc. - is a nice to have
+ Can freely discuss the latest papers and descend to fine details
+ Is reasonably opinionated
PROCESS
- Intro call with one of our Founding Engineers
- Technical Interview(s) with one of our Members of Engineering
- Team fit call with the People team
- Final interview with one of our Founding Engineers
Benefits
- Fully remote work & flexible hours
- 37 days/year of vacation & holidays
- Health insurance allowance for you and dependents
- Company-provided equipment
- Wellbeing, always-be-learning and home office allowances
- Frequent team get togethers
- Great diverse & inclusive people-first culture
About Poolside
In this decade, the world will create Artificial General Intelligence. There will only be a small number of companies who will achieve this. Their ability to stack advantages and pull ahead will define the winners. These companies will move faster than anyone else. They will attract the world's most capable talent. They will be on the forefront of applied research, engineering, infrastructure and deployment at scale. They will continue to scale their training to larger & more capable models. They will be given the right to raise large amounts of capital along their journey to enable this. They will create powerful economic engines. They will obsess over the success of their users and customers. Poolside exists to be this company - to build a world where AI will be the engine behind economically valuable work and scientific progress.
About Our Team
We are a remote-first team that sits across Europe and North America. We come together once a month in-person for 3 days, always Monday-Wednesday, with an open invitation to stay the whole week. We also do longer off-sites once a year. Our team is a combination of more research and more engineering-oriented profiles, however, everyone deeply cares about the quality of the systems we build and has a strong underlying knowledge of software development. We believe that good engineering leads to faster development iterations, which allows us to compound our efforts.
About The Role
You’ll be working on our data team focused on the quality of the datasets being delivered for training our models. This is a hands-on role where your #1 mission would be to improve the quality of the pretraining datasets by leveraging your previous experience, intuition and training experiments. This role particularly focuses on generating synthetic data at scale and determining the best strategies to leverage such data into training large models. You’ll closely collaborate with other teams like Pretraining, Posttraining, Evals, and Product to define high-quality data needs that map to missing model capabilities and downstream use cases. Staying in sync with the latest research in synthetic data generation and pretraining is key to success in this role. You will constantly lead original research initiatives through short, time-bounded experiments while deploying highly technical engineering solutions into production. With the volumes of data to process being massive, you'll have a performant distributed data pipeline together with a large GPU cluster at your disposal.
YOUR MISSION
To deliver large, high-quality, and diverse synthetic datasets mixing natural language and code modalities to train best-in-class coding agents.
Responsibilities
- Follow the latest research related to LLMs and synthetic data generation in particular. Be familiar with the most relevant open-source datasets and models.
- Design and implement complex pipelines that can generate large amounts of data while maintaining high diversity and optimizing the resources available.
- Closely work with other teams such as Pretraining, Posttraining, Evals and Product to ensure alignment on the quality of the models delivered.
- Continuously measure and refine the quality of the datasets being generated while validating the final data strategy through quantitative data ablation experiments.
Skills & Experience
- Strong machine learning and engineering background
- Experience with Large Language Models (LLM), including:
+ Understanding of how LLMs learn
+ Data ablations and scaling laws
+ Post-training techniques
+ Training reasoning and agentic models
- Experience with implementing cost-efficient, complex pipelines to generate synthetical datasets at scale optimizing for data quality, correctness, diversity, etc.
- Experience with evals tracking model capabilities (general knowledge, reasoning, math, coding, long-context, etc)
- Experience in building trillion-scale pretraining datasets, and familiarity with concepts like data curation, deduplication, data mixing, tokenization, curriculum, impact of data repetition, etc.
- Excellent programming skills in Python
- Strong prompt engineering skills
- Experience working with large-scale GPU clusters and distributed data pipelines
- Strong obsession with data quality
- Research experience:
+ Author of scientific papers on any of the topics: applied deep learning, LLMs, source code generation, etc. - is a nice to have
+ Can freely discuss the latest papers and descend to fine details
+ Is reasonably opinionated
PROCESS
- Intro call with one of our Founding Engineers
- Technical Interview(s) with one of our Members of Engineering
- Team fit call with the People team
- Final interview with one of our Founding Engineers
Benefits
- Fully remote work & flexible hours
- 37 days/year of vacation & holidays
- Health insurance allowance for you and dependents
- Company-provided equipment
- Wellbeing, always-be-learning and home office allowances
- Frequent team get togethers
- Great diverse & inclusive people-first culture
Job Roles at Poolside Companies
How to Get Visa Sponsorship in Poolside Visa Sponsorship USA
Target AI and machine learning roles specifically
Poolside's work centers on code-generating AI models, so roles in ML research, model training, and AI infrastructure align most naturally with their sponsorship profile. Focus your application on positions where your technical specialization directly supports their core product mission.
Emphasize deep research or engineering credentials
Poolside competes at the frontier of AI development, where advanced degrees and published research carry real weight. Highlighting graduate-level work in machine learning, compiler design, or systems engineering strengthens your case for both the role and H-1B specialty occupation requirements.
Move quickly, early-stage companies hire in focused bursts
As a growth-stage AI company, Poolside's hiring often reflects specific product milestones. Open roles can close fast. Monitor their careers page closely and apply promptly, as sponsorship decisions are typically made alongside initial offers at companies this size.
Search for Poolside on Migrate Mate to confirm current openings
Not every job posting clearly states whether sponsorship is available. Migrate Mate surfaces verified sponsors so you can filter by real sponsorship history and find Poolside's current roles alongside other confirmed H-1B sponsors in the AI and software space.
Prepare for a technical-first interview process
Poolside hires for highly specialized AI and software engineering roles. Their interview process is likely to be deeply technical. Demonstrating hands-on experience with large language models, code synthesis, or low-level systems will differentiate you from generalist candidates.
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Get Access To All JobsFrequently Asked Questions
Does Poolside sponsor H-1B visas?
Yes, Poolside sponsors H-1B visas for qualifying roles. As an AI research company focused on code-generating foundation models, their sponsored positions tend to be highly technical, covering areas like machine learning engineering, AI research, and software infrastructure. Confirming your role qualifies as a specialty occupation is an important early step in the application process.
What types of roles at Poolside are most likely to receive visa sponsorship?
Sponsorship at Poolside is concentrated in technical roles that directly support their AI research and product development. Machine learning engineers, research scientists, and software engineers working on model infrastructure or deployment are the most likely candidates. Roles requiring advanced expertise in large language models, systems programming, or AI tooling align best with their sponsorship profile.
How do I find current visa-sponsored jobs at Poolside?
Poolside's careers page lists open positions, but it doesn't always specify which roles include visa sponsorship. Migrate Mate is the most reliable way to find Poolside's sponsored openings in one place, with filtering by visa type and verified sponsorship history so you're not guessing which listings actually come with H-1B support.
What is the typical H-1B sponsorship timeline if I receive an offer from Poolside?
If you receive an offer requiring H-1B sponsorship, Poolside would need to file a Labor Condition Application with the Department of Labor before submitting your H-1B petition to USCIS. For cap-subject petitions, filing happens in April for an October 1 start date. Premium processing is available to reduce USCIS adjudication time to around 15 business days, though the LCA process runs on a separate timeline of roughly seven to ten business days.
Is Poolside a strong choice for international candidates seeking long-term sponsorship?
Poolside is an early-stage company with a focused technical mission, which means sponsored roles are meaningful but selective. For international candidates with strong AI or software engineering backgrounds, the company represents a real opportunity in a high-growth space. Growth-stage companies can offer a clearer path to continued sponsorship and eventual Green Card support as their headcount scales, though it's worth discussing long-term sponsorship plans directly during the hiring process.
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