Research Product Manager Jobs in USA with Visa Sponsorship
Research Product Managers sit at the intersection of user insights and product strategy, making them strong candidates for H-1B visa and O-1 visa sponsorship. The role qualifies as a specialty occupation requiring a bachelor's degree or higher in a related field, and employers in tech, healthcare, and financial services sponsor regularly. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsResearch Product Manager — AI Systems (Structured Data, Evaluation & Learning Efficiency)
About the Role
We’re hiring a Research Product Manager to define and build core systems that determine how AI models are evaluated, improved, and deployed on real-world data.
You’ll work on systems spanning:
- model evaluation and benchmarking
- post-training and feedback loops
- structured and relational data learning
- performance, efficiency, and cost optimization
This role sits at the intersection of ML infrastructure, research, and product. It is closest to roles like ML platform PM or AI infrastructure PM, but with deeper ownership of how systems are designed and how model performance translates into real-world outcomes.
You’ll partner closely with researchers and engineers to move ideas from experiments into production systems used at scale.
The Mission
AI today is no longer bottlenecked by model architecture alone.
The real constraints are:
- how models are evaluated
- how they improve after training
- how they behave in real-world systems
Granica is building the systems that solve this.
We are a research and systems company led by Prof. Andrea Montanari (Stanford), focused on:
- evaluation as a first-class system
- post-training as a continuous learning loop
- efficient learning over real-world data
Most real-world data is structured and relational, yet modern AI systems remain poorly optimized to learn from it.
Our thesis:
AI advantage will come from how efficiently models learn from structured data—and how that translates into economic value.
What You’ll Do
- Define and drive systems for model evaluation, benchmarking, and real-world performance
- Build product direction for post-training systems and feedback loops that continuously improve models
- Define how models learn from large-scale structured and relational datasets
- Partner with engineering to build systems that connect data platforms (warehouses, lakehouses) with ML systems
- Own how improvements move from research experiments into production systems
- Model trade-offs across compute, data efficiency, performance, and cost
- Identify where system improvements drive measurable business impact
Skills and Qualifications
Minimum Qualifications
- 5+ years of experience in product management, technical program management, or similar roles in AI, ML infrastructure, or data systems
- Strong understanding of machine learning systems, including training, evaluation, and deployment
- Experience working with large-scale data systems or distributed infrastructure
- Ability to reason about trade-offs across data, compute, performance, and cost
- Track record of driving complex technical systems from concept to production
Preferred Qualifications
- Experience with ML platforms, LLM systems, or AI infrastructure
- Experience with evaluation systems, observability, or model performance tooling
- Familiarity with structured or relational data systems (e.g., warehouses, lakehouses)
- Background in engineering, applied research, or ML systems development
- Experience operating in research-driven or highly ambiguous environments
Ideal Backgrounds
- ML / AI infrastructure PMs (OpenAI, Google, Meta, Snowflake, Databricks, AWS, or similar)
- Product leaders in model systems, evaluation, or observability
- Research engineers or applied scientists transitioning into product
- Engineers who have built ML or data systems and taken on product ownership
Why This Role Matters
Most AI systems are limited not by model capability, but by:
- weak evaluation systems
- inefficient learning loops
- poor utilization of structured data
- lack of connection between performance and real-world outcomes
This role defines how those constraints are solved in production systems. You won’t be optimizing features—you’ll be defining the systems that determine how models improve, how they are trusted, and how they deliver value.
Logistics
- Location: Mountain View, CA
- Work model: On-site, five days per week
- Level: Senior / Staff / Principal (depending on experience)
Compensation & Benefits
- Competitive salary, meaningful equity, and substantial bonus for top performers
- Flexible time off plus comprehensive health coverage for you and your family
- Support for research, publication, and deep technical exploration
At Granica, you will shape the fundamental infrastructure that makes intelligence itself efficient, structured, and enduring. Join us to build the foundational data systems that power the future of enterprise AI!
Research Product Manager — AI Systems (Structured Data, Evaluation & Learning Efficiency)
About the Role
We’re hiring a Research Product Manager to define and build core systems that determine how AI models are evaluated, improved, and deployed on real-world data.
You’ll work on systems spanning:
- model evaluation and benchmarking
- post-training and feedback loops
- structured and relational data learning
- performance, efficiency, and cost optimization
This role sits at the intersection of ML infrastructure, research, and product. It is closest to roles like ML platform PM or AI infrastructure PM, but with deeper ownership of how systems are designed and how model performance translates into real-world outcomes.
You’ll partner closely with researchers and engineers to move ideas from experiments into production systems used at scale.
The Mission
AI today is no longer bottlenecked by model architecture alone.
The real constraints are:
- how models are evaluated
- how they improve after training
- how they behave in real-world systems
Granica is building the systems that solve this.
We are a research and systems company led by Prof. Andrea Montanari (Stanford), focused on:
- evaluation as a first-class system
- post-training as a continuous learning loop
- efficient learning over real-world data
Most real-world data is structured and relational, yet modern AI systems remain poorly optimized to learn from it.
Our thesis:
AI advantage will come from how efficiently models learn from structured data—and how that translates into economic value.
What You’ll Do
- Define and drive systems for model evaluation, benchmarking, and real-world performance
- Build product direction for post-training systems and feedback loops that continuously improve models
- Define how models learn from large-scale structured and relational datasets
- Partner with engineering to build systems that connect data platforms (warehouses, lakehouses) with ML systems
- Own how improvements move from research experiments into production systems
- Model trade-offs across compute, data efficiency, performance, and cost
- Identify where system improvements drive measurable business impact
Skills and Qualifications
Minimum Qualifications
- 5+ years of experience in product management, technical program management, or similar roles in AI, ML infrastructure, or data systems
- Strong understanding of machine learning systems, including training, evaluation, and deployment
- Experience working with large-scale data systems or distributed infrastructure
- Ability to reason about trade-offs across data, compute, performance, and cost
- Track record of driving complex technical systems from concept to production
Preferred Qualifications
- Experience with ML platforms, LLM systems, or AI infrastructure
- Experience with evaluation systems, observability, or model performance tooling
- Familiarity with structured or relational data systems (e.g., warehouses, lakehouses)
- Background in engineering, applied research, or ML systems development
- Experience operating in research-driven or highly ambiguous environments
Ideal Backgrounds
- ML / AI infrastructure PMs (OpenAI, Google, Meta, Snowflake, Databricks, AWS, or similar)
- Product leaders in model systems, evaluation, or observability
- Research engineers or applied scientists transitioning into product
- Engineers who have built ML or data systems and taken on product ownership
Why This Role Matters
Most AI systems are limited not by model capability, but by:
- weak evaluation systems
- inefficient learning loops
- poor utilization of structured data
- lack of connection between performance and real-world outcomes
This role defines how those constraints are solved in production systems. You won’t be optimizing features—you’ll be defining the systems that determine how models improve, how they are trusted, and how they deliver value.
Logistics
- Location: Mountain View, CA
- Work model: On-site, five days per week
- Level: Senior / Staff / Principal (depending on experience)
Compensation & Benefits
- Competitive salary, meaningful equity, and substantial bonus for top performers
- Flexible time off plus comprehensive health coverage for you and your family
- Support for research, publication, and deep technical exploration
At Granica, you will shape the fundamental infrastructure that makes intelligence itself efficient, structured, and enduring. Join us to build the foundational data systems that power the future of enterprise AI!
See all 109+ Research Product Manager jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Research Product Manager roles.
Get Access To All JobsTips for Finding Visa Sponsorship as a Research Product Manager
Target companies with active research functions
Large tech firms, healthcare platforms, and fintech companies maintain dedicated user research and product teams that sponsor visas regularly. Prioritize organizations with in-house research infrastructure, as standalone product roles without a research function are harder to sponsor convincingly.
Document the degree-to-role connection clearly
USCIS scrutinizes Research PM roles because the job title spans multiple disciplines. A degree in cognitive science, human-computer interaction, information systems, or business with a research concentration strengthens the specialty occupation argument and reduces the chance of a request for evidence.
Differentiate yourself with mixed-methods research skills
Employers who sponsor visas want candidates who can run both qualitative and quantitative research independently. Fluency in user interviews, survey design, and behavioral data analysis makes you harder to replace and gives the company a stronger business necessity argument for sponsorship.
Expect O-1A to be a viable path if you have publications or speaking credits
Research PMs with published papers, conference presentations, or industry awards may qualify for the O-1A extraordinary ability visa. This bypasses the H-1B lottery entirely and is worth exploring with an immigration attorney before assuming the H-1B is your only option.
Understand the LCA and prevailing wage before negotiating
Your employer files a Labor Condition Application with the Department of Labor before sponsoring your visa. The LCA locks in a prevailing wage commitment, so understanding what wage level applies to your role and location helps you negotiate compensation that aligns with what the employer has already agreed to pay.
Browse sponsoring employers on Migrate Mate before applying broadly
Not every company willing to list a Research PM role is willing to sponsor a visa. Migrate Mate filters job listings to employers who actively sponsor, saving you the time of applying to companies that will decline at the offer stage when immigration comes up.
Research Product Manager jobs are hiring across the US. Find yours.
Find Research Product Manager JobsFrequently Asked Questions
Does a Research Product Manager role qualify for H-1B sponsorship?
Yes, Research Product Manager qualifies as a specialty occupation under H-1B requirements when the position requires a bachelor's degree or higher in a specific field such as cognitive science, human-computer interaction, information systems, or a related discipline. USCIS may issue a request for evidence if the job description is vague or lists a generic degree requirement, so the employer's petition should clearly explain why a specific degree field is necessary for the role.
What degree do I need to get sponsored as a Research Product Manager?
Most employers require a bachelor's degree in a field directly tied to research or product functions, such as human-computer interaction, cognitive science, psychology, computer science, or business with a research focus. A degree in an unrelated field can still qualify if you pair it with substantial work experience in research or product management, or if a credential evaluation establishes equivalency. Australian three-year bachelor's degrees are generally accepted as equivalent to a U.S. four-year degree for visa purposes.
How competitive is the H-1B lottery for Research Product Managers?
Research PM roles at cap-subject employers enter the general H-1B lottery alongside all other specialty occupations. In recent years, selection rates have hovered around 25%, meaning there is no guarantee of selection in any given year. Candidates with a U.S. master's degree or higher qualify for the advanced degree pool, which historically offers a modest selection advantage. If the lottery is a concern, explore cap-exempt employers such as universities or nonprofit research institutions, or investigate whether your experience supports an O-1A petition.
Which types of employers are most likely to sponsor a Research Product Manager?
Tech companies with dedicated UX research teams, healthcare platforms building patient-facing products, and financial services firms with consumer insights functions sponsor Research PMs most frequently. Companies that treat research as a core function rather than an outsourced service are more likely to pursue sponsorship because the role is harder to fill externally on short notice. Browse Migrate Mate to find employers who have already demonstrated willingness to sponsor this role.
Can I switch employers mid-visa as a Research Product Manager?
Yes, if you're on an H-1B you can change employers through H-1B portability, which allows you to start working for a new employer as soon as they file a new H-1B petition on your behalf, provided your current status is valid. The new employer must file a new Labor Condition Application and I-129 petition before or when you start. You do not need to reenter the lottery. The new role must still qualify as a specialty occupation, so ensure your new job description matches your degree field.
What is the prevailing wage requirement for sponsored Research Product Manager jobs?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.
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