Machine Learning Engineer

Captions is the leading video AI company, building the future of video creation. Over 10 million creators and businesses have used Captions to create videos for social media, marketing, sales, and more. We're on a mission to serve the next billion.

We are a rapidly growing team of ambitious, experienced, and devoted engineers, researchers, designers, marketers, and operators based in NYC. You'll join an early team and have an outsized impact on the product and the company's culture.

We’re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures (Series C lead), Kleiner Perkins (Series B lead), Sequoia Capital (Series A and Seed co-lead), Andreessen Horowitz (Series A and Seed co-lead), Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more.

Check out our latest financing milestone and some other coverage:

The Information: 50 Most Promising Startups

Fast Company: Next Big Things in Tech

The New York Times: When A.I. Bridged a Language Gap, They Fell in Love

Business Insider: 34 most promising AI startups

Time: The Best Inventions of 2024

** Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square) **

We’re seeking a Machine Learning Engineer with demonstrated experience deploying and scaling large generative models. As part of our engineering team, you’ll work on inference optimization, high-throughput pipelines, and model-serving architectures that bring SOTA video-generation technology to millions of users around the world. If you’re passionate about applying cutting-edge, multimodal foundational models at scale—this role is for you.

Responsibilities

• Deploy and optimize large generative models (e.g., diffusion, transformer-based) for real-time or batch inference.

• Build and maintain end-to-end ML pipelines, from data ingestion to model serving in production environments.

• Improve model performance through techniques like quantization, pruning, or distributed model inference.

• Collaborate closely with cross-functional teams (infrastructure, product, research) to integrate advanced ML features into our video creation platform.

• Implement MLOps best practices, including monitoring, logging, and robust CI/CD workflows for ML.

Preferred Qualifications

• 5+ years of industry experience deploying and scaling large generative or deep learning models in production.

• Strong software engineering skills in Python (or similar), with experience in cloud environments (AWS, GCP, or Azure).

• Expertise in deep learning frameworks (e.g., PyTorch, TensorFlow), with a focus on inference optimization and high-throughput serving.

• Familiarity with distributed training methods and large-scale data processing pipelines.

• A passion for practical, results-driven ML solutions—delivering tangible value to end users rather than purely research outcomes.

Join us if you’re excited to shape the future of generative video and unlock the potential of large-scale ML systems for creators worldwide!

Benefits:

• 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!

• Doordash DashPass subscription

• Health & Wellness Perks (Talkspace, Kindbody, One Medical subscription, HealthAdvocate, Teladoc)

• Multiple team offsites per year with team events every month

• Generous PTO policy and flexible WFH days

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.