Solutions Engineer — Media Generation
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AI Summary
About Artificial Analysis
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 35+, on track to triple by year end, backed by Nat Friedman (Github, Meta), Daniel Gross (SSI), Andrew Ng (Google Brain, DeepLearning.ai, Amazon), Adam D'Angelo (Quora, Poe, OpenAI), Clem Delangue (Hugging Face) and other industry leaders.
The Opportunity
Artificial Analysis benchmarks leading image and video generation models, providing the AI industry with independent quality and performance comparisons. Our media generation benchmarks rely on structured human preference evaluations to assess output quality across models.
We're hiring a Solutions Engineer to manage our media generation benchmarking pipeline. You'll run image and video generation evaluations, manage human preference studies, and serve as a technical point of contact for media generation model providers. This is a process-driven, operational role suited to someone who is detail-oriented, comfortable with Python, and can manage pipelines reliably day-to-day.
What You’ll Do
Generate image and video outputs across models according to standardized evaluation protocols
Set up and manage human preference evaluation studies, including study design, participant management, and quality control
Process and analyze preference vote data to produce benchmark results
Manage the end-to-end pipeline: from prompt execution through to published results
Serve as a technical point of contact for media generation model providers — communicating results, explaining methodology, and handling queries
Monitor data quality, flag anomalies, and ensure consistency across evaluation rounds
Maintain documentation of processes and configurations
Stay current with new image and video model releases
What We’re Looking For
Required:
3+ years of experience in a technical operations, data operations, or solutions engineering role
Comfortable with Python scripting and working with APIs
Experience managing research studies, data collection pipelines, or crowdsourcing platforms is a strong plus
Detail-oriented with strong process management skills — you can run recurring workflows reliably without oversight
Good written and verbal English communication skills
Responsive, organized, and dependable
Nice to have (not required):
Experience with image or video generation models (Midjourney, DALL-E, Stable Diffusion, Runway, Sora, etc.)
Background in data analysis or research operations
Familiarity with human evaluation methodologies or preference-based ranking systems
Experience in B2B SaaS or developer tools
Why Artificial Analysis?
Shape how AI gets built: The leading AI labs track our benchmarks and use them to guide their development priorities. Your work will directly influence the direction of AI.
Become a world expert in AI: You will evaluate every major model, across every major capability, as they are released. Very few roles offer this breadth of exposure to frontier AI.
Work with the most important players in AI: You'll manage relationships with teams at the leading AI labs and major enterprises as a trusted, independent voice.
Join at a defining moment: We're 35+ people and fast growing, backed by some of the most connected investors in AI. The people who join now will shape the product, the team, and the strategy as we scale.
Competitive compensation including equity
Our team is split across San Francisco, Sydney, and Melbourne
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