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.
Similar Jobs
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Serve as the primary post-implementation contact for top customers, craft joint success plans, run executive business reviews and workshops, mentor teammates, support French-speaking customers, and advise on customizing Samsara’s IoT platform to drive safety, efficiency, and sustainability.
Top Skills:
IotSamsara PlatformVehicle TelematicsVideo-Based Safety
Gaming
Lead product vision, roadmap, and outcomes for Hit It Rich Slots. Drive monetization and live-ops strategy, coordinate cross-functional teams and partners, define analytics standards, and own long-term player engagement, retention, and revenue growth.
Cloud • Fintech • Food • Information Technology • Software • Hospitality
Lead design and delivery of scalable ML systems across the full lifecycle for recommendations, forecasting, targeting, and personalization. Collaborate with engineers and product teams, set modeling and productionization standards, mentor data scientists, guide architecture and experimentation, and apply cloud and MLOps best practices to drive measurable product and business impact.
Top Skills:
AthenaAWSBedrockCi/CdDynamoDBGlueLlm Fine-TuningMl Ops FrameworksPythonPyTorchRlhfSagemakerScikit-LearnSQLTensorFlowVersion Control
What you need to know about the London Tech Scene
London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.
