The Research Engineer will design scalable evaluation systems for multimodal generative AI models, integrating metrics and automated pipelines for model assessment and improvement.
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
Luma is pushing the boundaries of generative AI, building tools that redefine how visual content is created. We're seeking a Research Engineer to design and scale the infrastructure that powers our model evaluation efforts. This role is about building the pipelines, metrics, and automated systems that close the loop between model output, evaluation, and improvement. You'll work across research, engineering, and product teams to ensure our models are measured rigorously, consistently, and in ways that directly inform development.
Responsibilities
- Design and implement scalable pipelines for automated evaluation of generative models, with a focus on visual and multimodal outputs (image, video, text, audio).
- Develop novel metrics and evaluation models that capture qualities like fidelity, coherence, temporal consistency, and alignment with human intent.
- Integrate evaluation signals into training loops (including reinforcement learning and reward modeling) to continuously improve model performance.
- Build infrastructure for large-scale regression testing, benchmarking, and monitoring of multimodal generative models.
- Collaborate with researchers running human studies to translate human evaluation frameworks into automated or semi-automated systems.
- Partner with model researchers to identify failure cases and build targeted evaluation harnesses.
- Maintain dashboards, reporting tools, and alerting systems to surface evaluation results to stakeholders.
- Stay current with emerging evaluation techniques in generative AI, multimodal LLMs, and perceptual quality assessment.
Qualifications
- Master's or PhD in Computer Science, Machine Learning, or a related technical field (or equivalent industry experience).
- 5+ years of experience building ML evaluation systems, model pipelines, or large-scale infrastructure.
- Hands-on experience working with visual data (images and/or video), including evaluation, modeling, or data preparation.
- Proficiency in Python and ML frameworks (PyTorch, JAX, or TensorFlow).
- Familiarity with human-in-the-loop evaluation workflows and how to scale them with automation.
- Strong background in machine learning, with experience in generative models (diffusion, LLMs, multimodal architectures).
- Strong software engineering skills (CI/CD, testing, data pipelines, distributed systems).
Nice to Have
- Experience with reinforcement learning or reward modeling.
- Prior work on perceptual metrics, multimodal evaluation benchmarks, or retrieval-based evaluation.
- Background in large-scale model training or evaluation infrastructure.
- Experience designing metrics for perceptual quality
- Familiarity with creative media workflows (film, VFX, animation, digital art).
- Contributions to open-source evaluation libraries or benchmarks.
The base pay range for this role is $190,000 – $375,000 per year.
About LumaLuma’s mission is to build unified general intelligence that can generate, understand, and operate in the physical world.
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.
Luma AI San Francisco, California, USA Office
San Francisco, CA, United States
Similar Jobs
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Manage enterprise customers after implementation, helping them achieve business value from Samsara’s IoT platform. Develop joint success plans, lead executive business reviews and customer workshops, recommend workflow improvements, explain platform capabilities, resolve barriers, and mentor Customer Success and Support teams. Collaborate with Sales, Support, Sales Engineering, Product, and Engineering while supporting customers across transportation, utilities, field services, and other physical-operation industries.
Top Skills:
Internet Of Things (Iot)SaaS
Artificial Intelligence • Fintech • Information Technology • Marketing Tech • Payments • Social Impact • Software
Leads and builds Donorbox’s product marketing function, owning positioning, messaging, product-led growth, launches, enablement, competitive intelligence, and performance measurement. Partners with Product, Sales, Customer Success, and Marketing to drive acquisition, conversion, retention, and expansion. Manages one direct report, establishes scalable processes and KPIs, influences roadmap priorities, and presents data-driven insights to executive leadership.
Top Skills:
Product-Led Growth (Plg)SaaS
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Lead and develop a Canada Scaled Customer Success team to drive onboarding, adoption, expansion, and renewals via digital scale programs. Hire and coach CSMs, manage KPIs/OKRs, improve processes and tooling, collaborate cross-functionally, and escalate high-stakes customer moments to ensure measurable customer outcomes.
Top Skills:
CRMCs PlatformDigital Engagement ToolsGainsightProduct AnalyticsTotango
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
