Product Manager (Media Generation - Image & Video)

Artificial Analysis•San Francisco, CA

1d•Onsite

About The Position

Artificial Analysis is the leading independent AI benchmarking company. We support labs, engineers and enterprises to understand AI capabilities and make critical decisions about their AI strategies. We are the go-to authority for understanding AI, from AI labs and enterprises to media, investors, and policymakers. Our benchmarks don’t just measure the cutting edge of AI, they are actively shaping the frontier. Our benchmarks and analysis are trusted by hundreds of thousands of users and are the go-to reference for leading AI labs including OpenAI, Google, Meta, NVIDIA and Anthropic, and major publications including the Wall Street Journal, Bloomberg, the Financial Times and The Economist. We are a team of 40+, on track to double by end of year, backed by Nat Friedman (GitHub, Meta), Daniel Gross (SSI, Meta), Andrew Ng (Google Brain, DeepLearning.ai , Amazon), Adam D’Angelo (Quora, Poe, OpenAI), Clem Delangue (Hugging Face) and other industry leaders. We’re hiring Product Managers focused on AI image and video generation. You’ll work closely with us to develop and enhance our media arenas and leaderboards, contributing to product strategy and execution at the frontier of generative media. This is a hands-on, technical product role: you’ll drive day-to-day operations for our image and video offerings and be a key contributor to product development, collaborating closely with engineering and analysis colleagues, as well as our founders. You’ll run human preference studies, curate prompt sets and categories, and work with the leading media generation companies to benchmark their latest models. We are open to a wide range of experience levels for this role and will shape the seat to the person.

Requirements

3+ years of professional experience
Strong analytical and critical thinking skills
Excitement about AI and eagerness to work at the forefront of technological innovation
Demonstrated excellence, both academically and professionally
Real interest in AI image and video generation

Nice To Haves

Experience at an AI image or video generation company (e.g. Midjourney, Runway, Black Forest Labs, Luma, Higgsfield, Ideogram, Krea, Recraft or similar) or a media generation team at a larger lab (e.g. OpenAI, Google), especially in product, operations or research roles
Experience building products leveraging image or video generation models
Familiarity with human preference evaluation methodologies or arena-style ranking systems
Experience in strategy consulting
Strong writing skills, especially in relation to explaining technical topics to both technical and non-technical audiences
Visual communication skills (e.g. making slides, visualizing data)
Proficiency in Python and data analysis libraries (e.g. pandas, numpy, matplotlib); experience with AI/ML frameworks (e.g. PyTorch, TensorFlow)

Responsibilities

Contribute to image and video product strategy and help execute the roadmap for our arenas and leaderboards, including video editing, reference-to-image and reference-to-video capabilities
Build prompt libraries, categories and evaluation techniques that reflect how creators and developers actually use image and video models, today and in the coming years
Keep coverage up to date by benchmarking new models and providers as they launch, managing generation pipelines and human preference studies
Deeply understand how creators and developers push these models, and translate those insights into evaluation frameworks that help users understand capability differences
Help amplify the impact of our media benchmarks, collaborating with our team to maximize impact of our content across platforms and audiences
Work with leading image and video companies to benchmark their models, understanding their capabilities and helping shape industry standards for how media generation is evaluated
Embrace an AI-native workflow, using cutting-edge AI tools to generate leverage in a fast-changing industry and maintain our competitive edge in AI benchmarking