Machine Learning Engineer, Mirage
$170-230k
Offers Equity
5 days a week in office (Union Square, NY)
AI-powered creative studio
Job no longer available
AI-powered creative studio
101-200 employees
Job no longer available
$170-230k
Offers Equity
5 days a week in office (Union Square, NY)
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
- 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)
- Familiarity with compression techniques (quantization, pruning, distillation) for large-scale models
- Experience profiling and optimizing model inference (batching, concurrency, hardware utilization)
- 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
- Exposure to diffusion models, multimodal video generation, or large-scale generative architectures
- Experience with distributed training frameworks (FSDP, DeepSpeed, Megatron-LM) or HPC environments
What the job involves
- 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
- 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
- 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
- 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
- Explore cutting-edge GPU acceleration frameworks (e.g., TensorRT, Triton, TorchServe) to continuously improve throughput and reduce costs
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.
Salary benchmarks
We don't have enough data yet to provide salary benchmarks for this role.
Submit your salary to help other candidates with crowdsourced salary estimates.
Share this job