Job Description
Mirage is the leading AI short-form video company. We’re building full-stack foundation models and products that redefine video creation, production and editing. Over 20 million creators and businesses use Mirage’s products to reach their full creative and commercial potential.
We are a rapidly growing team of ambitious, experienced, and devoted engineers, researchers, designers, marketers, and operators based in NYC. As an early member of our team, you’ll have an opportunity to have an outsized impact on our products and our company's culture.
Our Products
Captions
Mirage Studio
Our Technology
AI Research @ Mirage
Mirage Model Announcement
Seeing Voices (white-paper)
Press Coverage
TechCrunch
Lenny’s Podcast
Forbes AI 50
Fast Company
Our Investors
We’re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz , Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more.
** Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square)
We do not work with third-party recruiting agencies, please do not contact us**
About the role:
Captions is seeking a Machine Learning Engineer to partner closely with our Researchers and bring large-scale multimodal video diffusion models into production. You’ll be responsible for optimizing and deploying state-of-the-art generative models (tens to hundreds of billions of parameters) to deliver low-latency, high-throughput inference at scale. This is a unique opportunity to work on cutting-edge AI—spanning audio-video generation, diffusion architectures, and temporal modeling—and ensure these innovations reach millions of creators worldwide.
Responsibilities:
Inference & Deployment
Develop high-performance GPU-based inference pipelines for large multimodal diffusion models.
Build, optimize, and maintain serving infrastructure to deliver low-latency predictions at large scale.
Collaborate with DevOps teams to containerize models, manage autoscaling, and ensure uptime SLAs.
Model Optimization & Fine-Tuning
Leverage techniques like quantization, pruning, and distillation to reduce latency and memory footprint without compromising quality.
Implement continuous fine-tuning workflows to adapt models based on real-world data and feedback.
Production MLOps
Design and maintain automated CI/CD pipelines for model deployment, versioning, and rollback.
Implement robust monitoring (latency, throughput, concept drift) and alerting for critical production systems.
Performance & Scaling
Explore cutting-edge GPU acceleration frameworks (e.g., TensorRT, Triton, TorchServe) to continuously improve throughput and reduce costs.
Requirements:
Technical Expertise
Proven experience deploying deep learning models on GPU-based infrastructure (NVIDIA GPUs, CUDA, TensorRT, etc.).
Strong knowledge of containerization (Docker, Kubernetes) and microservice architectures for ML model serving.
Proficiency with Python and at least one deep learning framework (PyTorch, TensorFlow).
Model Optimization
Familiarity with compression techniques (quantization, pruning, distillation) for large-scale models.
Experience profiling and optimizing model inference (batching, concurrency, hardware utilization).
Infrastructure
Hands-on experience with ML pipeline orchestration (Airflow, Kubeflow, Argo) and automated CI/CD for ML.
Strong grasp of logging, monitoring, and alerting tools (Prometheus, Grafana, etc.) in distributed systems.
Domain Experience
Exposure to diffusion models, multimodal video generation, or large-scale generative architectures.
Experience with distributed training frameworks (FSDP, DeepSpeed, Megatron-LM) or HPC environments.
Comprehensive medical, dental, and vision plans
401K with employer match
Commuter Benefits
Catered lunch multiple days per week
Dinner stipend every night if you're working late and want a bite!
Grubhub subscription
Health & Wellness Perks (Talkspace, Kindbody, One Medical subscription, HealthAdvocate, Teladoc)
Multiple team offsites per year with team events every month
Generous PTO policy
Captions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Please note benefits apply to full time employees only.
Compensation Range: $175K - $275K
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