Snorkel AI Visa Sponsorship Jobs USA
Snorkel AI is a data-centric AI company building tools that help organizations programmatically label and manage training data. It operates in a competitive corner of the AI infrastructure space and has a track record of sponsoring skilled international talent, making it a credible option for H-1B visa and OPT holders in AI and machine learning roles.
Find Snorkel AI JobsOverview
Showing 5 of 33+ Snorkel AI Visa Sponsorship Jobs USA
See all 33+ Snorkel AI Visa Sponsorship Jobs USA
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Snorkel AI Visa Sponsorship Jobs USA.
Get Access To All JobsAbout Snorkel
At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!
About The Role
You'll be Snorkel's primary technical voice in the open-source and research communities. The work spans three audiences: frontier AI research teams (post-training, RL environments, evals and benchmarks), enterprise ML and applied AI teams building specialized models on proprietary expertise, and the broader data-centric AI community. You'll partner closely with our research, forward deployed research, and product teams to translate the methodology behind Snorkel's work into world-class technical content, open-source contributions, conference presence, and a thriving community of data-centric AI practitioners. Success looks like: a strong Snorkel open-source presence, a steady cadence of high-signal technical writing and research artifacts, marquee presence at the conferences that matter (NeurIPS, ICML, ICLR, AI Engineer World's Fair), and an engaged community of researchers and practitioners who view Snorkel as the trusted authority on data development for modern AI.
Responsibilities
- Own Snorkel's external technical voice. Write methodology posts, technical deep-dives, and research-grade content on data development for frontier models.
- Lead Snorkel's open-source presence. Define the GTM approach, ship code, review PRs, recruit contributors, and keep the libraries credible and current. Build OSS that demonstrates Snorkel's methodology in practice, including reproducible evals and benchmark artifacts.
- Advance the conversation on AI evaluation and benchmarking. Publish original work on how to measure agentic AI systems. Domain-specific evals, agent evals, LLM-as-judge calibration, contamination and saturation, and the connection between evals and post-training data.
- Drive conference and research community presence. Land talks, papers, and workshops at NeurIPS, ICML, ICLR, AI Engineer World's Fair, and the right practitioner venues. Build relationships with academic labs and AI research teams.
- Partner with the research team. Translate what's learned in research collaborations into externally shareable methodology, case studies, and tooling.
- Set the bar for technical credibility. Design evals and benchmarks, prototype RL environments, and write code worth using. Your authority comes from doing the work, not just talking about it.
Preferred Qualifications
- Experience. 6+ years in applied ML research, AI engineering, developer/research advocacy, or a research-intensive technical role with significant public output. Prior DevRel/advocate experience welcome but not required.
- Deep technical fluency in modern AI. Post-training techniques (RLHF, DPO, RLAIF), evaluation methodologies, RL environment design, training data pipelines, synthetic data generation, and at least one applied domain (coding agents, reasoning, multimodal, agents).
- Hands-on experience with AI evaluation and benchmarks. You've built and run real evals: public benchmarks (MMLU, GPQA, SWE-bench, HELM, BIG-bench, Arena-style head-to-heads), domain-specific custom evals, and LLM-as-judge pipelines with proper calibration.
- You build with AI, not just about AI. A power user of frontier coding agents (Claude Code, Cursor, Codex, and the like) in your day-to-day workflow, and you've built non-trivial agentic systems yourself – multi-step, tool-using, with real evals and an opinion on what breaks.
- A real public body of work. Talks, papers, blog posts, podcasts, and/or OSS contributions you can point to. Quality and signal matter more than volume.
- Customer- and researcher-facing presence. Comfortable in a room with frontier-lab research leads or a F500 ML team; can read the room and hold technical credibility on either side.
- Self-directed and comfortable with ambiguity. You ship without being asked, set your own quality bar, and enjoy moving at the pace of frontier AI.
Bonus: Advanced degree or sustained research output in ML/AI; prior experience at an AI lab, OSS-first AI company, or a research-driven technical org; conference program-committee or organizing experience; published or maintained a public benchmark; relationships in the post-training, evals, or RL-environments communities. Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location. Salary range(s) for this role $150,000—$200,000 USD.
Be Your Best at Snorkel
Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.
Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
About Snorkel
At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!
About The Role
You'll be Snorkel's primary technical voice in the open-source and research communities. The work spans three audiences: frontier AI research teams (post-training, RL environments, evals and benchmarks), enterprise ML and applied AI teams building specialized models on proprietary expertise, and the broader data-centric AI community. You'll partner closely with our research, forward deployed research, and product teams to translate the methodology behind Snorkel's work into world-class technical content, open-source contributions, conference presence, and a thriving community of data-centric AI practitioners. Success looks like: a strong Snorkel open-source presence, a steady cadence of high-signal technical writing and research artifacts, marquee presence at the conferences that matter (NeurIPS, ICML, ICLR, AI Engineer World's Fair), and an engaged community of researchers and practitioners who view Snorkel as the trusted authority on data development for modern AI.
Responsibilities
- Own Snorkel's external technical voice. Write methodology posts, technical deep-dives, and research-grade content on data development for frontier models.
- Lead Snorkel's open-source presence. Define the GTM approach, ship code, review PRs, recruit contributors, and keep the libraries credible and current. Build OSS that demonstrates Snorkel's methodology in practice, including reproducible evals and benchmark artifacts.
- Advance the conversation on AI evaluation and benchmarking. Publish original work on how to measure agentic AI systems. Domain-specific evals, agent evals, LLM-as-judge calibration, contamination and saturation, and the connection between evals and post-training data.
- Drive conference and research community presence. Land talks, papers, and workshops at NeurIPS, ICML, ICLR, AI Engineer World's Fair, and the right practitioner venues. Build relationships with academic labs and AI research teams.
- Partner with the research team. Translate what's learned in research collaborations into externally shareable methodology, case studies, and tooling.
- Set the bar for technical credibility. Design evals and benchmarks, prototype RL environments, and write code worth using. Your authority comes from doing the work, not just talking about it.
Preferred Qualifications
- Experience. 6+ years in applied ML research, AI engineering, developer/research advocacy, or a research-intensive technical role with significant public output. Prior DevRel/advocate experience welcome but not required.
- Deep technical fluency in modern AI. Post-training techniques (RLHF, DPO, RLAIF), evaluation methodologies, RL environment design, training data pipelines, synthetic data generation, and at least one applied domain (coding agents, reasoning, multimodal, agents).
- Hands-on experience with AI evaluation and benchmarks. You've built and run real evals: public benchmarks (MMLU, GPQA, SWE-bench, HELM, BIG-bench, Arena-style head-to-heads), domain-specific custom evals, and LLM-as-judge pipelines with proper calibration.
- You build with AI, not just about AI. A power user of frontier coding agents (Claude Code, Cursor, Codex, and the like) in your day-to-day workflow, and you've built non-trivial agentic systems yourself – multi-step, tool-using, with real evals and an opinion on what breaks.
- A real public body of work. Talks, papers, blog posts, podcasts, and/or OSS contributions you can point to. Quality and signal matter more than volume.
- Customer- and researcher-facing presence. Comfortable in a room with frontier-lab research leads or a F500 ML team; can read the room and hold technical credibility on either side.
- Self-directed and comfortable with ambiguity. You ship without being asked, set your own quality bar, and enjoy moving at the pace of frontier AI.
Bonus: Advanced degree or sustained research output in ML/AI; prior experience at an AI lab, OSS-first AI company, or a research-driven technical org; conference program-committee or organizing experience; published or maintained a public benchmark; relationships in the post-training, evals, or RL-environments communities. Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location. Salary range(s) for this role $150,000—$200,000 USD.
Be Your Best at Snorkel
Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.
Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Job Roles at Snorkel AI
See all 33+ Snorkel AI Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Snorkel AI roles.
Get Access To All JobsTips for Finding Snorkel AI Visa Sponsorship Jobs USA
Target AI and ML engineering roles first
Snorkel AI's core product sits at the intersection of machine learning and data labeling infrastructure. Roles in model development, ML engineering, and AI research are the most natural fit for sponsored positions, so prioritize those when applying.
Understand what Snorkel AI actually builds
Snorkel AI's platform focuses on programmatic data labeling and foundation model fine-tuning. Demonstrating fluency with weak supervision, LLM fine-tuning, or training data pipelines in your application signals you're genuinely aligned with the company's technical direction.
Look for OPT-friendly roles if you're on F-1
Snorkel AI has sponsored F-1 OPT workers, which means it's accustomed to supporting international students in STEM roles. If you're on OPT, flag your timeline early so the team can plan around potential STEM extension or H-1B transition needs.
Search verified sponsors before applying broadly
Not every AI startup is set up to sponsor visas. Migrate Mate surfaces verified sponsors so you can filter by real sponsorship history, helping you focus your energy on companies like Snorkel AI that have an established process for international hires.
Prepare for a technical-first interview process
Snorkel AI hires deeply technical candidates for its AI infrastructure product. Expect system design, ML fundamentals, and possibly domain-specific questions about data labeling or model training. Strong technical performance matters as much as cultural fit.
Engage with Snorkel AI's research and product community
Snorkel AI has roots in Stanford AI research and maintains a presence in the academic and enterprise AI communities. Engaging with their published work or open-source tools before applying can help you stand out in a technically competitive candidate pool.
Frequently Asked Questions
Does Snorkel AI sponsor H-1B visas?
Yes, Snorkel AI sponsors H-1B visas. The company has a track record of supporting international hires in technical roles, particularly in AI and machine learning. If you're targeting an H-1B sponsorship, focus on engineering and research positions, which align most closely with Snorkel AI's core product development needs.
What visa types does Snorkel AI sponsor?
Snorkel AI sponsors H-1B visas and supports F-1 OPT workers, including those in STEM fields who may need OPT extensions. The company has also sponsored TN visas, making it accessible to qualified Canadian and Mexican nationals. Its sponsorship activity is concentrated in technical and AI-focused roles rather than generalist positions.
Which roles or departments at Snorkel AI are most likely to receive visa sponsorship?
Sponsorship at Snorkel AI is most common in technical roles, particularly machine learning engineering, AI research, and software engineering focused on data infrastructure. Given the company's product focus on programmatic data labeling and foundation model tooling, candidates with hands-on ML or LLM experience are the strongest fit for sponsored positions.
How do I find open visa-sponsored roles at Snorkel AI?
The most reliable approach is to use Migrate Mate, which filters job listings by verified sponsorship history so you can see roles at companies like Snorkel AI that have an established track record of supporting international candidates. This saves time compared to applying broadly and hoping sponsorship is available on a case-by-case basis.
How do I approach the application timeline if I need H-1B sponsorship at Snorkel AI?
H-1B sponsorship involves USCIS filing deadlines tied to the annual lottery, with registrations typically opening in March and the fiscal year starting October 1. If you're on OPT, start conversations with Snorkel AI's recruiting team well before your work authorization expires so there's enough runway to file on time. Being transparent about your timeline from the first interview helps avoid last-minute complications.