Research engineer/Scientist- Post Training at Luma AI

Palo Alto, California, United States

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$250,000 – $300,000Compensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, Machine LearningIndustries

Requirements

Advanced degree (Master's or PhD) in Computer Science, Artificial Intelligence, Machine Learning, or related technical discipline with concentrated study in deep learning and computer vision methodologies
Demonstrated ability to do independent research in Academic or Industry settings
Substantial industry experience in large-scale deep learning model training, with demonstrated expertise in at least one of Large Language Models, Vision-Language Models, Diffusion Models, or comparable generative AI architectures
Comprehensive technical proficiency and practical experience with leading deep learning frameworks, including advanced competency in one of PyTorch, JAX, TensorFlow, or equivalent platforms for model development and optimization
Strong orientation toward applied AI implementations with emphasis on translating product requirements into technical solutions, coupled with exceptional visual discrimination and dedicated focus on enhancing visual fidelity and aesthetic quality of generated content
Proficiency in accelerated prototyping and demonstration development for emerging features, facilitating efficient iteration cycles and comprehensive stakeholder evaluation prior to production implementation
Established track record of effective cross-functional teamwork, including successful partnerships with teams spanning Product, Design, Evaluation, Applied, and creative specialists

Responsibilities

Optimize Luma's image and video generative models through targeted fine-tuning to improve visual quality, instruction adherence, and overall performance metrics
Implement reinforcement learning techniques including Direct Preference Optimization and Generalized Reward Preference Optimization to align model outputs with human preferences and quality standards
Partner closely with the Applied Research team to identify product requirements, understand diverse use cases across Luma's platforms, and execute targeted fine-tuning initiatives to address performance gaps and enhance user-facing capabilities
Conduct comprehensive side-by-side evaluations comparing model performance against leading market competitors, systematically analyzing the impact of post-training techniques on downstream performance metrics and identifying areas for improvement
Develop advanced post-training capabilities for Luma’s video models including Camera control, Object & character Reference, Image & Video Editing, Human Performance & Motion Transfer Approaches
Architect data processing pipelines for large-scale video and image datasets, implementing filtering, balancing, and captioning systems to ensure training data quality across diverse content categories
Research and deploy cutting-edge diffusion sampling methodologies and hyperparameter optimization strategies to achieve superior performance on established visual quality benchmarks
Research emerging post-training methodologies in generative AI, evaluate their applicability to Luma's product ecosystem, and integrate promising techniques into our Post-training recipe

Skills

Fine-tuning

Reinforcement Learning

Direct Preference Optimization

Generalized Reward Preference Optimization

Diffusion Sampling

Hyperparameter Optimization

Data Processing Pipelines

Multimodal Models

Video Generation

Image Generation

Model Evaluation

Luma AI

Develops multimodal AI technologies for creativity

About Luma AI

Luma AI develops multimodal artificial intelligence technologies that enhance human creativity and capabilities. Their main product, the Dream Machine, allows users to interact with various types of data, enabling creative professionals, businesses, and developers to explore innovative applications of AI. Unlike many competitors, Luma AI focuses on integrating multiple modes of interaction, which broadens the possibilities for users. The company operates on a subscription model, providing access to its AI tools and services, and aims to lead the way in AI-driven creativity and productivity.

San Francisco, CaliforniaHeadquarters

2021Year Founded

$84.9MTotal Funding

LATE_VCCompany Stage

Consumer Software, AI & Machine LearningIndustries

51-200Employees

Benefits

Company Equity

Stock Options

Risks

Competition from Google's Veo 2 and OpenAI's Sora Turbo challenges Luma AI's market position.

AWS's cost-reducing features may make Luma AI's services less competitive.

AI-generated content controversies could harm Luma AI's reputation if outputs are misleading.

Differentiation

Luma AI transforms text into 3D models, enhancing user interaction with digital content.

The Dream Machine integrates multimodal AI, offering a unique creative platform for users.

Luma AI's Photon models provide high-quality, personalized image generation capabilities.

Upsides

Luma AI's $90 million funding boosts its capacity for innovation and market expansion.

Dream Machine 1.5's advanced text-to-video features attract creative professionals and businesses.

Expanding Dream Machine into a mobile app increases accessibility and user engagement.

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