Staff Engineer Jobs at Reflection AI with Visa Sponsorship
Staff Engineer jobs at Reflection AI sit at the core of building frontier AI research infrastructure. The company sponsors select work visa categories, making it a viable path for international engineers with deep systems or ML infrastructure experience who are ready to operate at a high level of technical ownership.
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Get Access To All JobsOur Mission
Reflection’s mission is to build open superintelligence and make it accessible to all. We’re developing open weight models for individuals, agents, enterprises, and even nation states. Our team of AI researchers and company builders come from DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic and beyond.
About The Role
Data is playing an increasingly crucial role at the frontier of AI innovation. Many of the most meaningful advances in recent years have come not from new architectures, but from better data. As a member of the Data Team, your mission is to build and operate the ingestion systems that turn the open web and other large-scale data sources into reliable, well-structured corpora for training frontier models. You will own the machinery that acquires, extracts, normalizes, versions, and delivers data to our pre-training pipelines. You’ll work directly with world-class researchers to close the loop between what we collect and how it impacts model performance. This role is ideal for engineers who love building robust distributed systems, but who also want to run experiments, reason about tradeoffs in data acquisition, and iterate quickly based on measurable impact. Working closely with our pre-training and data quality teams, you will:
- Build and operate large-scale data ingestion systems for pre-training, including web crawling, extraction, and dataset delivery
- Run experiments to evaluate crawling strategies, extraction methods, and ingestion tradeoffs
- Analyze ingested data to identify gaps, redundancy, and areas to improve
- Build ingestion pipelines that scale reliably across large data campaigns
- Develop specialized crawlers for high-priority data sources
- Review code, debug production issues, and continuously improve ingestion infrastructure
About You
- Curious about how training data influences model capabilities, and can iterate quickly based on measurable downstream impact
- Able to collaborate tightly across functions: researchers, infra, operations, and external partners
- Enjoy working in a hybrid research–engineering role
Skills And Qualifications
- Experience building web crawling, data ingestion, or large-scale data acquisition systems using Ray, Beam, Spark, or similar technologies
- Familiarity with how LLMs are trained and evaluated, and an intuition for what makes data useful for training
- Comfortable working with very large datasets (multi-TB to PB scale) and building systems that are observable, testable, and maintainable
- Comfortable designing experiments and using data to guide system improvements
- Excellent communication skills. You can explain system behavior. You consider and communicate tradeoffs clearly
What We Offer
We believe that to build superintelligence that is truly open, you need to start at the foundation. Joining Reflection means building from the ground up as part of a small talent-dense team. You will help define our future as a company, and help define the frontier of open foundational models. We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported.
- Top-tier compensation: Salary and equity structured to recognize and retain the best talent globally
- Health & wellness: Comprehensive medical, dental, vision, life, and disability insurance
- Life & family: Fully paid parental leave for all new parents, including adoptive and surrogate journeys. Financial support for family planning
- Benefits & balance: paid time off when you need it, relocation support, and more perks that optimize your time
- Opportunities to connect with teammates: lunch and dinner are provided daily. We have regular off-sites and team celebrations
Our Mission
Reflection’s mission is to build open superintelligence and make it accessible to all. We’re developing open weight models for individuals, agents, enterprises, and even nation states. Our team of AI researchers and company builders come from DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic and beyond.
About The Role
Data is playing an increasingly crucial role at the frontier of AI innovation. Many of the most meaningful advances in recent years have come not from new architectures, but from better data. As a member of the Data Team, your mission is to build and operate the ingestion systems that turn the open web and other large-scale data sources into reliable, well-structured corpora for training frontier models. You will own the machinery that acquires, extracts, normalizes, versions, and delivers data to our pre-training pipelines. You’ll work directly with world-class researchers to close the loop between what we collect and how it impacts model performance. This role is ideal for engineers who love building robust distributed systems, but who also want to run experiments, reason about tradeoffs in data acquisition, and iterate quickly based on measurable impact. Working closely with our pre-training and data quality teams, you will:
- Build and operate large-scale data ingestion systems for pre-training, including web crawling, extraction, and dataset delivery
- Run experiments to evaluate crawling strategies, extraction methods, and ingestion tradeoffs
- Analyze ingested data to identify gaps, redundancy, and areas to improve
- Build ingestion pipelines that scale reliably across large data campaigns
- Develop specialized crawlers for high-priority data sources
- Review code, debug production issues, and continuously improve ingestion infrastructure
About You
- Curious about how training data influences model capabilities, and can iterate quickly based on measurable downstream impact
- Able to collaborate tightly across functions: researchers, infra, operations, and external partners
- Enjoy working in a hybrid research–engineering role
Skills And Qualifications
- Experience building web crawling, data ingestion, or large-scale data acquisition systems using Ray, Beam, Spark, or similar technologies
- Familiarity with how LLMs are trained and evaluated, and an intuition for what makes data useful for training
- Comfortable working with very large datasets (multi-TB to PB scale) and building systems that are observable, testable, and maintainable
- Comfortable designing experiments and using data to guide system improvements
- Excellent communication skills. You can explain system behavior. You consider and communicate tradeoffs clearly
What We Offer
We believe that to build superintelligence that is truly open, you need to start at the foundation. Joining Reflection means building from the ground up as part of a small talent-dense team. You will help define our future as a company, and help define the frontier of open foundational models. We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported.
- Top-tier compensation: Salary and equity structured to recognize and retain the best talent globally
- Health & wellness: Comprehensive medical, dental, vision, life, and disability insurance
- Life & family: Fully paid parental leave for all new parents, including adoptive and surrogate journeys. Financial support for family planning
- Benefits & balance: paid time off when you need it, relocation support, and more perks that optimize your time
- Opportunities to connect with teammates: lunch and dinner are provided daily. We have regular off-sites and team celebrations
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Get Access To All JobsTips for Finding Staff Engineer Jobs at Reflection AI
Align your portfolio to frontier AI infrastructure
Reflection AI hires Staff Engineers to own large-scale systems problems, not feature work. Before applying, document your experience with distributed training, model serving, or ML platform engineering at scale. Shallow breadth won't move you past the technical screen.
Confirm your visa category fits Staff Engineer timelines
E-3 and TN visas can be filed quickly and don't require USCIS lottery selection, which matters when an offer moves fast. If you're on F-1 OPT, verify your remaining authorization window before your start date to avoid gaps.
Surface sponsorship compatibility early in conversations
Bring up your visa category during the recruiter screen, not after the offer. Reflection AI sponsors specific visa types, and confirming fit early prevents late-stage complications that can collapse an otherwise strong offer.
Prepare your specialty occupation documentation thoroughly
For E-3 or H-1B filings, USCIS requires the role to qualify as a specialty occupation. Staff Engineer positions at AI research companies typically meet this bar, but your degree field needs to align with the technical scope of the role.
Use Migrate Mate to target open Staff Engineer roles
Reflection AI posts Staff Engineer openings across several technical domains, and the lineup shifts regularly. Use Migrate Mate to filter and track open roles at Reflection AI filtered by visa type, so you're applying to live positions that match your authorization.
Coordinate your LCA filing window with your employer
Your employer files the Labor Condition Application with DOL before your visa petition can proceed. At a fast-moving company like Reflection AI, confirm internally who owns this step and what the typical turnaround looks like so you're not caught waiting at the wrong moment.
Frequently Asked Questions
Does Reflection AI sponsor H-1B visas for Staff Engineers?
Reflection AI's confirmed sponsorship includes E-3 visa, F-1 OPT, F-1 CPT, and TN visas for Staff Engineer roles. H-1B visa sponsorship has not been confirmed for this role based on available filing data. Australian citizens and Canadian or Mexican nationals in eligible occupations have the clearest sponsorship pathway here. If H-1B is your primary route, verify directly with the recruiter before investing time in the process.
How do I apply for Staff Engineer jobs at Reflection AI?
Applications go through Reflection AI's careers page, where Staff Engineer openings are listed by technical domain. Before applying, tailor your resume to reflect systems-level ownership at scale, as the bar for Staff roles is high. Migrate Mate also indexes Reflection AI's open Staff Engineer positions filtered by visa sponsorship type, which helps you confirm eligibility before submitting.
Which visa types are commonly used for Staff Engineer roles at Reflection AI?
Reflection AI sponsors E-3, F-1 OPT, F-1 CPT, and TN visas for Staff Engineer positions. The E-3 is available exclusively to Australian citizens and offers a straightforward consular process with no lottery. TN applies to Canadian and Mexican nationals in qualifying USMCA occupations. F-1 OPT and CPT cover students and recent graduates within their authorized work period.
What qualifications does Reflection AI expect for Staff Engineer candidates?
Staff Engineer roles at Reflection AI sit above senior-level and require demonstrated ownership of large-scale technical systems. Hiring patterns reflect demand for deep expertise in distributed systems, ML infrastructure, or compiler and runtime engineering. A relevant bachelor's or advanced degree is expected, and your degree field needs to align with the technical scope of the specific role for visa specialty occupation purposes.
How do I time my visa filing if I receive an offer from Reflection AI?
E-3 and TN visas can move quickly once the offer is confirmed, sometimes within a few weeks. F-1 OPT requires that your employment start date falls within your authorized period, so check your I-20 end date and any grace period implications before signing. Your employer's legal team will initiate the Labor Condition Application with DOL, which must be certified before the visa petition proceeds.