Join Mirage as a Research Engineer to advance agentic systems for creative tasks in a collaborative AI video company.
Posted by employer 1 day ago
First seen on Joblaze 1 day ago
Last verified on the company career page 1 day ago
Skills & Technologies
What you'll build
- Design and build end-to-end agentic systems for creative tasks
- Develop novel approaches for training and adapting large language models
- Design new objectives, datasets, and fine-tuning strategies
- Run systematic experiments to evaluate agent performance
- Analyze failure modes across the full agent loop
Must have
- BS/MS/PhD in CS, ML, or related field
- Strong track record building production ML systems
- Deep understanding of transformers and modern LLM techniques
- Experience with fine-tuning, alignment, or post-training methods
- Comfort owning the full stack
Practical constraints
- Must be in-person at NYC HQ
AI in the day-to-day
Develop new approaches for building and extending agentic systems that understand and operate over complex, real-world data, particularly video.
Requirements
- Education
- Master's degree
Not disclosed in this posting: compensation, years of experience, visa sponsorship.
Benefits
Joblaze summary
In this role, the Research Engineer will focus on developing and enhancing agentic systems that leverage large language models for creative tasks, particularly in video. Key skills include a strong background in machine learning, experience with transformers, and the ability to design and implement end-to-end systems. This position is well-suited for individuals with advanced degrees in computer science or related fields, who have a proven track record in building production ML systems. The team at Mirage is dedicated to pushing the boundaries of AI in creative media, fostering an environment of innovation.
Joblaze insights
- Listed yesterday — first seen on Joblaze September 29, 2026. Last confirmed on Mirage's careers page September 29, 2026.
- This exact title is also open at 1 other location at Mirage: Union Square, New York City.
- Machine Learning appears in 11.1% of 458 comparable mid ai/ml roles in United States; Transformers appears in 0.9% of 458 comparable mid ai/ml roles in United States.
Quick facts
- Is the Research Engineer, Agentic Systems role remote?
- No — this is an on-site role in New York City, United States.
- Where is the role based?
- Mirage is hiring for this position in New York City, United States.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Large Language Models, Machine Learning, Transformers.
- What seniority level is this role?
- Mirage targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Research Engineer, Agentic Systems role at Mirage.
From the original posting
About the Role
Mirage is seeking an ML Engineer to push the boundaries of large language models for multimodal creative tasks. You'll develop new approaches for building and extending agentic systems that understand and operate over complex, real-world data, particularly video.
This role focuses on advancing agent capabilities, improving reasoning and control, and enabling new forms of interaction between language models and time-based media.
Responsibilities
Design and build end-to-end agentic systems for creative tasks
Develop novel approaches for training and adapting the large language models that power these agents
Design new objectives, datasets, and fine-tuning strategies to improve agent behavior and reliability
Explore multimodal reasoning and structured generation for creative control
Run systematic experiments to evaluate and improve agent performance in real-world tasks
Design evaluation frameworks for agentic workflows in video analysis and editing
Analyze failure modes across the full agent loop (planning, tool use, execution) and iterate on improvements
What makes you a great fit
BS/MS/PhD in CS, ML, or related field
Strong track record building production ML systems or agentic pipelines
Deep understanding of transformers and modern LLM techniques
Experience with fine-tuning, alignment, or post-training methods, especially for adapting models to generate structured outputs or drive tool use
Comfort owning the full stack, from model-level experiments to deployed agent systems
Strong experimental rigor and good taste for what makes agents actually work in practice
Benefits:
Comprehensive medical, dental, and vision plans
401K with employer match
Commuter Benefits
Catered lunch multiple days per week
Grubhub subscription
Health & Wellness Perks
Generous PTO policy
Standard company text repeated across Mirage's postings is omitted here.