Member of Technical Staff, Mirage
Training Data Infrastructure
$215-300k
+ Equity
Office located in Union Square, NY
AI-powered creative studio
Be an early applicant
AI-powered creative studio
101-200 employees
Be an early applicant
$215-300k
+ Equity
Office located in 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
- Bachelor's or Master's degree in Computer Science, Machine Learning, or related field
- 3+ years experience in ML infrastructure development or large-scale data engineering
- Strong programming skills, particularly in Python and distributed computing frameworks
- Expertise in building and optimizing high-throughput data pipelines
- Proven experience with video/image data pre-processing and feature engineering
- Deep knowledge of machine learning workflows, including model training and data loading systems
- Track record in performance optimization and system scaling
- Experience with cluster management and distributed computing
- Background in MLOps and infrastructure monitoring
- Demonstrated ability to build reliable, large-scale data processing systems
- Love tackling hard technical problems head-on
- Take ownership while knowing when to loop in teammates
- Get excited about improving system performance
- Want to work directly with researchers and engineers who are equally passionate about building great systems
What the job involves
- 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
- Captions seeks an exceptional Research Engineer (MOTS) to drive innovation in training data infrastructure
- You'll conduct research on and develop sophisticated distributed training workflows and optimized data processing systems for massive video and multimodal datasets
- Beyond pure performance, you'll develop deep insight into our data to maximize training effectiveness
- As an early member of our ML Research team, you'll build foundational systems that directly impact our ability to train models powering video and multimodal creation for millions of users
- You'll work directly alongside our research and engineering teams in our NYC office
- We've intentionally built a culture where infrastructure and data work is highly valued - your success will be measured by the reliability and performance of our systems, not by your ability to navigate politics
- We're a team that loves diving deep into technical problems and emerging with practical solutions
- Build performant pipelines for processing video and multimodal training data at scale
- Design distributed systems that scale seamlessly with our rapidly growing video and multimodal datasets
- Create efficient data loading systems optimized for GPU training throughput
- Implement comprehensive telemetry for video processing and training pipelines
- Create foundation data processing systems that intelligently cache and reuse expensive computations across the training pipeline
- Build robust data validation and quality measurement systems for video and multimodal content
- Design systems for data versioning and reproducing complex multimodal training runs
- Develop efficient storage and compute patterns for high-dimensional data and learned representations
- Own and improve end-to-end training pipeline performance
- Build systems for efficient storage and retrieval of video training data
- Build frameworks for systematic data and model quality improvement
- Develop infrastructure supporting fast research iteration cycles
- Build tools and systems for deep understanding of our training data characteristics
- Build infrastructure enabling rapid testing of research hypotheses
- Create systems for incorporating user feedback into training workflows
- Design measurement frameworks that connect model improvements to user outcomes
- Enable systematic experimentation with direct user feedback loops
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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