Research Engineer

Research Engineer - Evaluations

Luma AI

Location:
United States; United Kingdom , Palo Alto ▼
London

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

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.

Job Responsibility:

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

Requirements:

Master's or PhD in Computer Science, Machine Learning, or a related technical field (or equivalent industry experience)
3+ 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

Additional Information:

Job Posted:
January 13, 2026

Employment Type:

Fulltime

Work Type:

Hybrid work

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