Member of Technical Staff, Mirage
Model Evaluation
$160-250k
Offers Equity
Office located in Union Square, New York City
AI-powered creative studio
Job no longer available
AI-powered creative studio
101-200 employees
Job no longer available
$160-250k
Offers Equity
Office located in Union Square, New York City
101-200 employees
Company mission
To empower our customers, regardless of background or experience, with the ability to bring their vision to life in seconds.
Role
Who you are
- Master's or PhD in Computer Science, Machine Learning, or related field
- Track record of research contributions at top ML conferences (NeurIPS, ICML, ICLR)
- Demonstrated experience implementing and improving upon state-of-the-art architectures
- Deep expertise in generative modeling approaches (diffusion, autoregressive, VAEs, etc.)
- Strong background in optimization techniques and loss function design
- Experience with empirical scaling studies and systematic architecture research
- Strong proficiency in modern deep learning tooling (PyTorch, CUDA, Triton, FSDP, etc.)
- Experience training diffusion models with 10B+ parameters
- Experience with very large language models (200B+ parameters) is a plus
- Deep understanding of attention, transformers, and modern multimodal architectures
- Expertise in distributed training systems and model parallelism
- Proven ability to implement and improve complex model architectures
- Track record of systematic empirical research and rigorous evaluation
- Ability to write clean, modular research code that scales
- Strong software engineering practices including testing and code review
- Experience with rapid prototyping and experimental design
- Strong analytical skills for debugging model behavior and training dynamics
- Facility with profiling and optimization tools
- Track record of bringing research ideas to production
- Experience maintaining high code quality in a research environment
What the job involves
- Captions is seeking an exceptional Research Engineer (MOTS) to advance the state-of-the-art in large-scale multimodal video diffusion models
- You'll conduct novel research on generative modeling architectures, develop new training techniques, and scale models to billions of parameters
- As a key member of our ML Research team, you'll work at the cutting edge of multimodal generation while building systems that enable natural, controllable video creation
- We're already training large-scale models with demonstrated product impact, and we're excited to continue expanding the scope and capabilities of our research
- We're especially excited about pushing the boundaries of audio-video generation, with a focus on realistic and charismatic human behavior that enables natural storytelling and creative iteration
- Our models power creative tools used by millions of creators, and we're tackling fundamental challenges in how to generate compelling human motion, expression, and speech
- Design and implement novel architectures for large-scale video and multimodal diffusion models
- Develop new approaches to multimodal fusion, temporal modeling, and video control
- Research temporal video editing techniques and controllable generation
- Research and validate scaling laws for video generation models
- Create new loss functions and training objectives for improved generation quality
- Drive rapid experimentation with model architectures and training strategies
- Validate research directly through product deployment and user feedback
- Train and optimize models at massive scale (10s-100s of billions of parameters)
- Develop sophisticated distributed training approaches using FSDP, DeepSpeed, Megatron-LM
- Design and implement model surgery techniques (pruning, distillation, quantization)
- Create new approaches to memory optimization and training efficiency
- Research techniques for improving training stability at scale
- Conduct systematic empirical studies of architecture and optimization choices
- Advance state-of-the-art in video model architecture design and optimization
- Develop new approaches to temporal modeling for video generation
- Create novel solutions for multimodal learning and cross-modal alignment
- Research and implement new optimization techniques for generative modeling and sampling
- Design and validate new evaluation metrics for generation quality
- Systematically analyze and improve model behavior across different regimes
Our take
As AI integration grows in creative fields, concerns arise about the future of professions like writing and design. However, Mirage, formerly Cpations, has transformed these anxieties into opportunities by harnessing AI technology to streamline the creative workflow.
By automating tasks in music, graphic design, and video production, Mirage allows users to generate compelling content directly from their mobile devices. With a focus on meeting the rising demand for captivating digital content, its subscription-based model covers key processes like captioning, editing, dubbing, and soundtracking.
Mirage's innovative approach has garnered attention, securing funding from tech giants like Sequoia Capital and Andreessen Horowitz. This investment will grow the company's machine learning team and invest further into technical infrastructure and in-house research efforts. It's the latter that spurned the company's rebrand from Captions in 2025, unifying the offerings of AI video platform Captions and the recently launched Mirage Studio under one name. It is refocusing on AI research into multimodal foundational models, which will help it differentiate itself in a highly competitive AI video solutions market.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (2 rounds)
Jul 2024
$60m
SERIES C
Jun 2023
$25m
SERIES B
Total funding: $85m
Company benefits
- Comprehensive medical, dental, and vision plans
- Anything you need to do your best work
- We’ve done team off-sites to places like Paris, London, Park City, Los Angeles, and Nashville with more planned in the future
Company HQ
Civic Center, New York, NY
Leadership
Gaurav Misra
(Co-Founder & CEO)Previously the Head of Design Engineering at Snap Inc, Senior Software Engineer at Localytics, Software Development Engineer at Microsoft, and Software Engineer at Lattice Engines.
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