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.
The Roles Mission
Bridge the gap between research and production by turning cutting-edge algorithms into scalable training systems. You will design and optimize the core infrastructure behind frontier AI models — from reinforcement learning training loops and distributed GPU training to massive-scale data pipelines. Our systems train models across thousands of GPUs and process petabyte-scale datasets. We care deeply about numerical stability, throughput, and reproducibility.
What This Team Does
This team owns and evolves the core infrastructure behind our training systems.
We Focus On
- Reinforcement learning training infrastructure
- Distributed training and inference systems
- Experiment infrastructure and reproducibility
- Large-scale data pipelines
The goal is to build the engineering foundation that allows researchers to iterate quickly while training models at massive scale.
About The Role
You will architect and optimize the core training infrastructure that powers our models. This includes RL training loops, distributed GPU systems, and large-scale data pipelines. You will work closely with researchers to transform new ideas into reliable, scalable training systems.
Responsibilities Include
- Designing and optimizing large-scale training loops and data pipelines.
- Implementing state-of-the-art techniques and ensuring they are numerically stable and computationally efficient.
- Building internal tooling for launching, monitoring, and reproducing complex experiments.
- Diagnosing deep bottlenecks across the training stack (GPU memory issues, communication overhead, dataloader stalls).
- Translating research prototypes into reusable, production-grade infrastructure.
What You'll Work With
Distributed Training
- GPU parallelism (data, tensor, pipeline, expert)
- Large-scale distributed training infrastructure
- Communication optimization (NCCL, RDMA, GPU interconnects)
- FSDP / ZeRO and model sharding
Orchestration & Runtime Systems
- Ray, Kubernetes, Slurm
- Distributed runtimes and async systems
- Containerization and sandboxing
Frameworks
- PyTorch
- JAX
- Megatron-style training stacks
- Triton / custom kernels
Data Infrastructure
- Large-scale dataset curation pipelines
- Deduplication and filtering systems
- Tokenization and preprocessing
- Distributed data processing frameworks
About You
- You are a strong software engineer who speaks the language of machine learning.
- You may not have a PhD, but you know how to implement a research paper.
- You have deep experience in at least one of the following: Distributed Training & Inference or Data Infrastructure.
- You enjoy working at the boundary between:
+ Machine learning algorithms
+ Distributed systems
+ High-performance computing
- You care deeply about performance, numerical stability, and reproducibility.
- You thrive in high-agency environments and enjoy solving hard technical problems.
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.
The Roles Mission
Bridge the gap between research and production by turning cutting-edge algorithms into scalable training systems. You will design and optimize the core infrastructure behind frontier AI models — from reinforcement learning training loops and distributed GPU training to massive-scale data pipelines. Our systems train models across thousands of GPUs and process petabyte-scale datasets. We care deeply about numerical stability, throughput, and reproducibility.
What This Team Does
This team owns and evolves the core infrastructure behind our training systems.
We Focus On
- Reinforcement learning training infrastructure
- Distributed training and inference systems
- Experiment infrastructure and reproducibility
- Large-scale data pipelines
The goal is to build the engineering foundation that allows researchers to iterate quickly while training models at massive scale.
About The Role
You will architect and optimize the core training infrastructure that powers our models. This includes RL training loops, distributed GPU systems, and large-scale data pipelines. You will work closely with researchers to transform new ideas into reliable, scalable training systems.
Responsibilities Include
- Designing and optimizing large-scale training loops and data pipelines.
- Implementing state-of-the-art techniques and ensuring they are numerically stable and computationally efficient.
- Building internal tooling for launching, monitoring, and reproducing complex experiments.
- Diagnosing deep bottlenecks across the training stack (GPU memory issues, communication overhead, dataloader stalls).
- Translating research prototypes into reusable, production-grade infrastructure.
What You'll Work With
Distributed Training
- GPU parallelism (data, tensor, pipeline, expert)
- Large-scale distributed training infrastructure
- Communication optimization (NCCL, RDMA, GPU interconnects)
- FSDP / ZeRO and model sharding
Orchestration & Runtime Systems
- Ray, Kubernetes, Slurm
- Distributed runtimes and async systems
- Containerization and sandboxing
Frameworks
- PyTorch
- JAX
- Megatron-style training stacks
- Triton / custom kernels
Data Infrastructure
- Large-scale dataset curation pipelines
- Deduplication and filtering systems
- Tokenization and preprocessing
- Distributed data processing frameworks
About You
- You are a strong software engineer who speaks the language of machine learning.
- You may not have a PhD, but you know how to implement a research paper.
- You have deep experience in at least one of the following: Distributed Training & Inference or Data Infrastructure.
- You enjoy working at the boundary between:
+ Machine learning algorithms
+ Distributed systems
+ High-performance computing
- You care deeply about performance, numerical stability, and reproducibility.
- You thrive in high-agency environments and enjoy solving hard technical problems.
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.
See all Staff Engineer Jobs at Reflection AI
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Staff Engineer Jobs at Reflection AI.
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.