Member of Technical Staff, Mirage
ML Ops
$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
- Bachelor's or Master's degree in Computer Science, Machine Learning, or related field
- Strong programming skills in Python and systems programming
- Experience with distributed systems and scalable infrastructure
- Track record of building reliable, performant large-scale ML systems
- Areas of Expertise (Strong experience in some or all of these areas):
- Deep expertise in PyTorch internals and distributed training frameworks (FSDP, DeepSpeed)
- GPU cluster management and optimization
- Performance profiling and systems optimization
- CUDA programming and kernel optimization
- Containerization and orchestration (Docker, Kubernetes)
- ML model serving and deployment at scale
- Language models and attention mechanism optimization
- Video and audio processing pipelines
- Large-scale diffusion models
- Love diving deep into complex systems optimization challenges
- Take ownership of critical infrastructure while collaborating effectively
- Get excited about pushing the boundaries of ML system performance
- Want to work directly with researchers on cutting-edge ML problems
- Thrive in fast-paced, research-driven environments
What the job involves
- Captions seeks an exceptional MLOps Research Engineer (MOTS) to architect and scale the machine learning infrastructure for our rapidly growing creative platform used by millions
- You'll own the development of our distributed training systems, optimize our rapidly growing GPU clusters, and build performant inference pipelines that power our cutting-edge multimodal video diffusion models
- As a key member of our ML Research team in a fast-growing Series C startup, you'll create foundational infrastructure enabling rapid research iteration while maintaining production-grade reliability and efficiency
- We're already training large-scale models and are excited to dramatically expand our infrastructure capabilities
- Develop and optimize distributed training frameworks integrating multiple modalities (video, audio, text, and structured metadata)
- Build flexible systems for cross-modal training orchestration and efficient experimentation
- Design reproducible training environments with versioned dependencies and configurations
- Implement comprehensive testing frameworks for validating model training correctness and performance
- Create infrastructure for systematic model quality assessment and performance benchmarking
- Design and implement flexible training orchestration systems that balance research agility with large-scale model training
- Build robust monitoring and observability systems for complex training and inference pipelines
- Design and manage GPU clusters optimized for distributed training of multimodal models
- Build out comprehensive automated metrics collection and alerting across our ML stack
- Profile and optimize model training throughput using mixed precision, gradient checkpointing, and advanced memory techniques
- Develop custom CUDA and Triton kernels to accelerate critical compute paths
- Implement creative solutions for cost optimization across spot instances and reserved capacity
- Design and optimize real-time inference systems enabling fast research iteration cycles
- Build infrastructure enabling rapid testing of research hypotheses
- Create systems supporting close collaboration between infrastructure and research teams
- Develop frameworks for reproducible research experimentation
- Enable seamless deployment of research innovations to production
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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