Applied Computer Vision Engineer
At a glance
Mid-level Machine Learning Engineering role at SpreeAI. San Francisco · full-time · no salary stated · we estimate $185,750–$272,875.
SpreeAI has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Build and keep preprocessing flows running for segmentation, pose estimation, human parsing and body mapping
- Check and standardize incoming data so downstream models receive consistent inputs
- Compare new vision models, connect them to the system and test them on internal evaluation datasets
- Review dataset quality and resolve the issues those checks uncover
- Turn research from ML scientists into pipelines that run regularly in production
What you bring
- You have hands-on experience delivering production computer vision work with Python and PyTorch
- You have worked with segmentation or pose estimation and shipped pipelines beyond research
- You can take responsibility for data quality and model evaluation, not only training
Who this fits
This role suits a mid-level engineer who wants to own production computer vision pipelines and work closely with ML scientists. The position is based in San Francisco and follows a hybrid arrangement.
From the employer
SPREEAI is a fast-growing, innovative AI company at the forefront of fashion and e-commerce, revolutionizing how consumers engage with fashion through lifelike photorealistic try-on technology and hyper-personalized shopping experiences. Our mission is to redefine the retail landscape with cutting-edge AI solutions that blend high fashion and technology. We thrive in a dynamic, fast-paced environment where creativity meets technology to drive real impact. If you are passionate about innovation and shaping the future of fashion, SPREEAI offers a platform to make your mark.
About the Role
SPREEAI builds AI virtual try-on that fashion brands embed in their sites and apps. Every try-on starts with the same question: did we read the person and the garment correctly? This role owns the computer vision pipelines that answer it, from preprocessing through evaluation, and keeps them reliable in production.
What you'll do
- Build and maintain preprocessing pipelines for try-on: segmentation, pose estimation, human parsing, and body mapping
- Validate and standardize inputs so downstream models get clean, consistent data
- Benchmark and integrate new vision models, and measure how they perform on our own evaluation datasets
- Run dataset quality checks and fix the failures they surface
- Work with ML scientists to move research into pipelines that run every day
Qualifications
- Hands-on production experience in applied computer vision with Python and PyTorch
- Experience with segmentation or pose estimation and a record of shipping pipelines, not only research
- Comfort owning data quality and evaluation, not just model training
- Comfort working in a fast-moving startup, in San Francisco (hybrid)
Why Join SPREEAI?
- Real ownership: a small team where the pipelines you build run in production for brand partners
- Hard, visible problems: accurate try-on across a wide range of people and garments
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