Luma AI Visa Sponsorship Jobs USA
Luma AI is an AI video and 3D generation company pushing the boundaries of visual AI technology. It sponsors select high-skill visa categories, making it a targeted option for international candidates with strong technical backgrounds looking to break into cutting-edge AI research and product development in the U.S.
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Get Access To All JobsAbout Luma AI
Luma’s mission is to build AGI. We believe that intelligence emerges from large-scale foundation models that can reason, plan, and communicate with depth and precision. Language models are central to this vision — serving as the backbone for reasoning, world modeling, and interaction. To advance this mission, we build and operate the full stack end-to-end, spanning foundation models, large-scale training infrastructure, inference systems, and real-world products. This tight integration allows us to push research forward while shipping impactful systems at scale. Backed by a recent $900M Series C and our partnership with Humain to build a 2 GW compute supercluster (Project Halo), we are scaling the next generation of frontier language models.
Where You Come In
This is a rare opportunity to help define the future of large-scale language models. You will work across the entire lifecycle of model development — from large-scale pre-training, to targeted mid-training, to post-training alignment and capability refinement. You will operate at the frontier of scaling laws, reasoning, and alignment, directly shaping how foundation models learn, generalize, and behave in real-world deployments.
What You’ll Do
This role spans both the “science” and “engineering” dimensions of research — two aspects that are equally important. You will work across modeling, data, systems, and evaluation.
Modeling:
- Architect and scale large autoregressive language models.
- Design improved pre-training objectives to enhance reasoning, knowledge retention, and compositional generalization.
- Develop mid-training strategies such as continued pre-training, domain adaptation, curriculum learning, and synthetic data integration.
- Advance post-training techniques, including instruction tuning, preference optimization, reinforcement learning, distillation, and inference-time compute scaling.
- Study and improve long-context modeling, planning depth, and multi-step reasoning behavior.
Data:
- Curate and construct massive, high-quality text corpora for pre-training.
- Design synthetic data pipelines for reasoning, tool use, mathematics, coding, and structured problem solving.
- Develop filtering, mixture weighting, and curriculum strategies that shape emergent capabilities.
- Formulate new tasks that improve coherence, logical consistency, factual grounding, and robustness.
Systems:
- Train frontier-scale language models across large GPU clusters.
- Optimize distributed training (data, tensor, pipeline parallelism), mixed precision, and memory efficiency.
- Build infrastructure for large-scale experimentation, ablations, and reproducibility.
- Improve inference efficiency and support scalable deployment.
Evaluation:
- Define and build evaluation frameworks for language intelligence, including:
- Multi-step reasoning and mathematical problem solving
- Coding and structured generation
- Knowledge grounding and factuality
- Planning and agentic behavior
- Instruction following and alignment
- Track capability development across pre-training, mid-training, and post-training.
- Close the loop between evaluation signals and data/model improvements.
Who You Are
- Strong foundation in machine learning and large language models.
- Deep understanding of autoregressive transformers and large-scale training dynamics.
- Experience with pre-training large models and/or post-training techniques such as instruction tuning, RLHF, preference optimization, or distillation.
- Hands-on experience with PyTorch and distributed training at scale.
- Comfortable operating across research and production environments.
What Sets You Apart (Bonus Points)
- Experience training frontier-scale language models from scratch.
- Research contributions in scaling laws, reasoning, alignment, or inference-time compute.
- Experience designing large-scale synthetic reasoning data.
- Expertise in long-context modeling or structured reasoning systems.
- Experience optimizing models for real-world deployment constraints.
Your application are reviewed by real people.
About Luma AI
Luma’s mission is to build AGI. We believe that intelligence emerges from large-scale foundation models that can reason, plan, and communicate with depth and precision. Language models are central to this vision — serving as the backbone for reasoning, world modeling, and interaction. To advance this mission, we build and operate the full stack end-to-end, spanning foundation models, large-scale training infrastructure, inference systems, and real-world products. This tight integration allows us to push research forward while shipping impactful systems at scale. Backed by a recent $900M Series C and our partnership with Humain to build a 2 GW compute supercluster (Project Halo), we are scaling the next generation of frontier language models.
Where You Come In
This is a rare opportunity to help define the future of large-scale language models. You will work across the entire lifecycle of model development — from large-scale pre-training, to targeted mid-training, to post-training alignment and capability refinement. You will operate at the frontier of scaling laws, reasoning, and alignment, directly shaping how foundation models learn, generalize, and behave in real-world deployments.
What You’ll Do
This role spans both the “science” and “engineering” dimensions of research — two aspects that are equally important. You will work across modeling, data, systems, and evaluation.
Modeling:
- Architect and scale large autoregressive language models.
- Design improved pre-training objectives to enhance reasoning, knowledge retention, and compositional generalization.
- Develop mid-training strategies such as continued pre-training, domain adaptation, curriculum learning, and synthetic data integration.
- Advance post-training techniques, including instruction tuning, preference optimization, reinforcement learning, distillation, and inference-time compute scaling.
- Study and improve long-context modeling, planning depth, and multi-step reasoning behavior.
Data:
- Curate and construct massive, high-quality text corpora for pre-training.
- Design synthetic data pipelines for reasoning, tool use, mathematics, coding, and structured problem solving.
- Develop filtering, mixture weighting, and curriculum strategies that shape emergent capabilities.
- Formulate new tasks that improve coherence, logical consistency, factual grounding, and robustness.
Systems:
- Train frontier-scale language models across large GPU clusters.
- Optimize distributed training (data, tensor, pipeline parallelism), mixed precision, and memory efficiency.
- Build infrastructure for large-scale experimentation, ablations, and reproducibility.
- Improve inference efficiency and support scalable deployment.
Evaluation:
- Define and build evaluation frameworks for language intelligence, including:
- Multi-step reasoning and mathematical problem solving
- Coding and structured generation
- Knowledge grounding and factuality
- Planning and agentic behavior
- Instruction following and alignment
- Track capability development across pre-training, mid-training, and post-training.
- Close the loop between evaluation signals and data/model improvements.
Who You Are
- Strong foundation in machine learning and large language models.
- Deep understanding of autoregressive transformers and large-scale training dynamics.
- Experience with pre-training large models and/or post-training techniques such as instruction tuning, RLHF, preference optimization, or distillation.
- Hands-on experience with PyTorch and distributed training at scale.
- Comfortable operating across research and production environments.
What Sets You Apart (Bonus Points)
- Experience training frontier-scale language models from scratch.
- Research contributions in scaling laws, reasoning, alignment, or inference-time compute.
- Experience designing large-scale synthetic reasoning data.
- Expertise in long-context modeling or structured reasoning systems.
- Experience optimizing models for real-world deployment constraints.
Your application are reviewed by real people.
Job Roles at Luma AI
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Get Access To All JobsTips for Finding Luma AI Visa Sponsorship Jobs USA
Target roles that align with Luma AI's core AI research focus
Luma AI's sponsorship activity centers on highly specialized technical work. Focus your applications on machine learning, computer vision, and 3D generation roles where your skills directly support the company's product roadmap, these are the positions most likely to attract sponsorship consideration.
Understand which visa types Luma AI actively supports
Luma AI sponsors H-1B and F-1 work authorization, including OPT and CPT. If you're on an F-1 visa, applying during OPT is a natural entry point, it lowers the immediate burden on the employer before an H-1B filing becomes necessary.
Demonstrate rare, specialized skills in your application materials
At a company working on frontier AI technology, sponsorship decisions often hinge on whether your skill set is genuinely hard to find domestically. Emphasize depth in areas like neural rendering, generative models, or real-time 3D, specificity signals you're not easily replaceable.
Time your outreach around Luma AI's hiring cycles
H-1B cap-subject petitions must be filed in April for an October start. If you're targeting Luma AI for H-1B sponsorship, aim to secure an offer by late winter or early spring. Starting conversations in Q4 of the prior year gives both sides enough runway.
Use Migrate Mate to find verified open roles at Luma AI
Filtering job boards for genuine sponsors wastes time. Migrate Mate surfaces verified sponsors so you can filter by real sponsorship history, helping you confirm Luma AI is actively hiring for roles that match your visa type before you invest effort in applying.
Prepare to clearly articulate your immigration timeline upfront
Luma AI is a focused, fast-moving team. Recruiters there appreciate candidates who come prepared with a clear picture of their current status, OPT expiration date, and H-1B eligibility, it removes ambiguity and signals professionalism during early conversations.
Frequently Asked Questions
Does Luma AI sponsor H-1B visas?
Yes, Luma AI does sponsor H-1B visas. Its sponsorship activity is concentrated on specialized technical roles in AI and computer vision. Because Luma AI is a smaller, focused company, it sponsors selectively rather than at high volume, so candidates with highly differentiated technical skills are best positioned to be considered for H-1B support.
Which visa types does Luma AI support for international workers?
Luma AI sponsors H-1B visas and supports F-1 work authorization, including both OPT and CPT. It does not have a documented track record of sponsoring Green Cards or E-3 visas. F-1 candidates are a natural fit given the OPT pathway provides immediate work authorization while the company evaluates longer-term sponsorship options.
Which departments or roles at Luma AI are most likely to receive visa sponsorship?
Sponsorship at Luma AI is most common in technical roles directly tied to its core product: machine learning engineering, computer vision research, 3D generation, and related software engineering positions. Non-technical roles such as marketing or operations are less likely to be supported, as sponsorship decisions reflect where the company's specialized hiring needs are hardest to fill domestically.
How do I find open visa-sponsored jobs at Luma AI?
The most efficient approach is to use Migrate Mate, which aggregates roles from verified sponsoring employers and lets you filter by visa type and company. This saves you from manually researching whether a posting actually includes sponsorship. Once you identify a relevant opening at Luma AI, apply directly and flag your visa status clearly in your initial communication with the recruiter.
How do I approach the application process at Luma AI as an international candidate?
Lead with your technical depth rather than your visa situation. Luma AI hires for highly specialized capabilities, so your application materials should make your expertise in relevant areas immediately clear. Once you reach the recruiter screen, be transparent about your current visa status, your OPT or H-1B timeline, and any upcoming deadlines, this allows the team to plan around your situation rather than being surprised by it mid-process.