Mirage
Software Engineer, ML Products
About this role
Mirage is seeking a Software Engineer to design and build agentic systems that power creative workflows in an AI-native video editing platform. You'll work across product, ML, and systems engineering to develop agents that execute creative tasks reliably at scale, integrating state-of-the-art models and measuring quality in production.
What you'll do
- Build and deploy end-to-end agentic systems that improve creative workflows while balancing quality, performance, and reliability
- Design agent architectures including context gathering, planning, tool selection, and task execution
- Integrate cutting-edge models combining internal research and external capabilities
- Measure and optimize agent quality using experimentation, evaluation frameworks, and production feedback
- Own meaningful problems end-to-end across product, ML, and systems domains
What they're looking for
- ML systems and agentic pipeline development in production
- Context engineering (RAG systems, token optimization, context management)
- Evaluation systems and agentic infrastructure design
- Multi-agent architectures
- LLM fine-tuning
- Problem solving and rapid learning
- End-to-end project ownership
- Fast-paced environment execution
Benefits
- Comprehensive medical, dental, and vision insurance
- 401K with employer match
- Commuter benefits
- Catered lunch multiple days per week
- Dinner stipend every night
- In-person NYC HQ (Union Square)
Opens the application — the Jobs AI extension fills it for you. Set up autofill
Opens the official application on the employer’s site. No login required.
Mirage
Mirage builds an AI-native video platform that leverages generative media and large language models to enable sophisticated video production, editing, and creative workflows. The company is hiring backend engineers, full-stack software engineers, ML engineers, and iOS developers to advance their AI-driven platform and enhance user experiences in web-based and mobile media creation.
View all jobs at MirageLikely interview questions
- Walk us through a production ML system or agentic pipeline you designed—how did you approach reliability and quality measurement?
- What's your experience building RAG systems and managing context at scale, and how did you optimize for both quality and latency?