---
title: 'Research Scientist / Engineer – Performance Optimization at Luma'
canonical: 'https://feeny.ai/job/research-scientist-engineer-performance-optimization-luma-sf-bay-area-q924ewctahqx'
type: 'job'
last_seen: '2026-09-11'
---

# Research Scientist / Engineer – Performance Optimization at Luma

- **Company:** Luma
- **Location:** Sf Bay Area, CA
- **Compensation:** $188k–$395k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2025-02-20
- **Last confirmed live:** 2026-09-11
- **Apply:** https://jobs.gem.com/lumalabs-ai/a2feb190-455d-45e6-b488-7ac840f30fbd

## Job description

## About Luma AI

Luma's mission is to build multimodal AI to expand human imagination and capabilities. We believe that multimodality is critical for intelligence. To go beyond language models and build more aware, capable and useful systems, the next step function change will come from vision. So we are working on training and scaling up multimodal foundation models for systems that can see and understand, show and explain, and eventually interact with our world to effect change.

## About the Role

The Performance Optimization team at Luma is dedicated to maximizing the efficiency and performance of our AI models. Working closely with both research and engineering teams, this group ensures that our cutting-edge multimodal models can be trained efficiently and deployed at scale while maintaining the highest quality standards.

## Responsibilities

- Profile and optimize GPU/CPU/Accelerator code for maximum utilization and minimal latency
- Write high-performance PyTorch, Triton, CUDA, deferring to custom PyTorch operations if necessary
- Develop fused kernels and leverage tensor cores and modern hardware features for optimal hardware utilization on different hardware platforms
- Optimize model architectures and implementations for distributed multi-node production deployment
- Build performance monitoring and analysis tools and automation
- Research and implement cutting-edge optimization techniques for transformer model

## Experience

- Expert-level proficiency in Triton/CUDA programming and GPU optimization
- Strong PyTorch skills
- Experience with PyTorch kernel development and custom operations
- Proficiency with profiling tools (NVIDIA Nsight, torch profiler, custom tooling)
- Deep understanding of transformer architectures and attention mechanisms
- (Preferred) Experience with compilers/exporters such as torch.compile, TensorRT, ONNX, XLA
- (Preferred) Experience optimizing inference workloads for latency and throughput
- (Preferred) Experience with Triton compiler and kernel fusion techniques
- (Preferred) Knowledge of warp-level intrinsics and advanced CUDA optimization

Your applications are reviewed by real people.

## About Luma

## Company Overview
- **One-liner**: Luma builds multimodal AI models that can generate, understand, and operate in the physical world, shipping them in products like Dream Machine for creators and teams.
- **Entity Type**: Private (Series C)
- **Headquarters**: Redwood City, California, USA
- **Founded**: 2021
- **Founders**: Not publicly listed on official sources

## Core Business
- **Primary industry**: Artificial Intelligence / Generative AI / Creative AI
- **Target customers**: B2B (enterprises, agencies, developers) and B2C (creators, filmmakers)
- **Mission or purpose statement**: To build unified general intelligence that can generate, understand, and operate in the physical world.

## Products & Services
- **Luma Dream Machine**: Consumer-facing product for turning ideas into compelling visuals (video, image, audio, text) using generative AI.
- **Ray 3.2 API**: Production-grade video generation API with full creative control—multi-keyframe (up to 16), V2V up to 20 seconds, reframe, 1080p output, native HDR, and 16-bit EXR export.
- **Uni-1.1 API**: Multimodal reasoning model API for image generation (text-to-image, reference-guided) and natural-language image editing, with up to nine reference inputs per request.
- **Luma Agents**: Agentic creative workflows that plan, generate, iterate, and refine across every stage of creative work—available in the Luma App and trusted by teams at Publicis Groupe, Serviceplan, Mazda, Dentsu, and Humain.
- **Open Physical AI Lab**: An open science effort to solve generalization in physical AI, built in the open for the benefit of all humanity.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metrics**: Total Funding: $1.3B+ (official site) / $1.057B (LinkedIn); Annual Revenue: $5M (LinkedIn estimate); Users worldwide: 30M+; Team Members: 250+
- **Notable Investors/Partners**: HUMAIN (led Series C), Andreessen Horowitz (led Series B), Amplify Partners (led Series A), Matrix (led Seed Round). Partners include Envato, Comfy, Runware, Flora, Krea, Magnific, Fal, LovArt.
- **Growth Signals**: 250+ team members, 30M+ users, $1.3B+ total funding, 45% yearly LinkedIn follower growth, recent product launches (Ray3.2, Uni-1.1, Luma Skills, Wonder Project partnership), $900M Series C raised November 2025.

## Competitive Advantages
- **Full-stack AI**: Luma builds its own foundation models end-to-end, rather than wrapping third-party models—giving it unique control over quality, latency, and cost.
- **Multimodal reasoning**: Uni-1 understands intention and responds to direction, not just prompts—offering brand intelligence at the model level.
- **Cinematic-grade output**: Ray 3.2 delivers 1080p, native HDR, 16-bit EXR export—production-ready for professional film and advertising pipelines.
- **Open science commitment**: The Open Physical AI Lab publishes research openly, attracting top-tier research talent and fostering community trust.
- **Speed & cost**: Claims less than half the price and latency of comparable models.

## Strategic Focus
- **Scaling enterprise adoption**: Custom deployment for creative teams at scale across advertising, film, and gaming production pipelines.
- **Agentic workflows**: Building Luma Agents as a force multiplier for creative teams—automating repetitive tasks while maintaining brand consistency.
- **Physical AI research**: Advancing the Open Physical AI Lab to solve generalization in physical AI, bridging digital generation with real-world operation.
- **API ecosystem growth**: Expanding the developer platform with two tiers (Build and Scale) and SDKs for Python and JavaScript/TypeScript.

## Why Work Here
- **Culture & mission**: "We believe real-world physics is the path to general intelligence. We unite research, product, and go-to-market into one engine." Described as a "lean, high-achieving team" building the future of creative intelligence.
- **Compensation & benefits**: Competitive compensation, 100% covered medical/dental/vision for employee and family, $1,500/year learning stipend, catered meals, team events, home office setup.
- **Work mode**: On-site roles in Redwood City, CA with additional offices in New York, NY; Los Angeles, CA; and international locations (Munich, Paris, London, Berlin).
- **Engineering culture**: Emphasis on shipping frontier research directly into products—"frontier research ships straight into the hands of working creatives." Hiring across research, systems engineering, infrastructure, design, and product.
- **Hiring process**: Transparent and fast—aims to complete within 2-3 weeks. Application review within a week, then recruiter screen, hiring manager interview, and team/leadership interviews.
- **Employee ratings**: 4.1/5.0 on LinkedIn (9 reviews)—Work-Life: 3.6, Compensation: 4.4, Culture: 4.1, Career: 4.2.
- **Open roles**: 46+ open positions including Forward Deployed Engineer, Research Scientist, Software Engineer, Robotics Engineer, Simulation Researcher, Site Reliability Engineer, Product Marketing Manager, Enterprise Account Executive, and more.

## Sources
1. [lumalabs.ai - Careers](https://lumalabs.ai/careers)
2. [lumalabs.ai - Official Site](https://lumalabs.ai/)
3. [lumalabs.ai - LLM Info](https://lumalabs.ai/llm-info)
4. [LinkedIn - Luma](https://linkedin.com/company/lumalabsai)

## Other roles at Luma

- [Research Scientist / Engineer – Reinforcement Learning Infrastructure](https://feeny.ai/job/research-scientist-engineer-reinforcement-learning-infrastructure-luma-sf-bay-v3kqd6ee41ag) — Sf Bay Area, CA
- [Tech Lead Manager, Inference](https://feeny.ai/job/tech-lead-manager-inference-luma-sf-bay-area-wv3qjs47nghh) — Sf Bay Area, CA
- [Creative Technologist](https://feeny.ai/job/creative-technologist-luma-london-1edm2ph4be1t) — London, United Kingdom
- [Sales Manager - West Coast](https://feeny.ai/job/sales-manager-west-coast-luma-los-angeles-qdhxhg06y85x) — Los Angeles, CA
- [Forward Deployed Engineer (EU)](https://feeny.ai/job/forward-deployed-engineer-eu-luma-london-h5nr5x8w2bhd) — London, United Kingdom
- [Product Manager, Applied Research](https://feeny.ai/job/product-manager-applied-research-luma-sf-bay-area-tgmbcragfeqt) — Sf Bay Area, CA
- [Product Manager, Core Product](https://feeny.ai/job/product-manager-core-product-luma-sf-bay-area-dx7f4b6fnr4d) — Sf Bay Area, CA
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- [Product Marketing Manager](https://feeny.ai/job/product-marketing-manager-luma-sf-bay-area-s0n3bqsd0qy1) — Sf Bay Area, CA