Computer Vision ML Researcher
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Job Description
As a Computer Vision / ML Researcher at Nagish you will lead the development and deployment of models that power our video generation sign language animation transcription and gesture segmentation efforts. You will collaborate across teams to build models that are indistinguishable from human interpreters and help scale our impact through automation and cutting-edge research.
On a day to day you will:
- Use and extend models for pose estimation gesture segmentation sign language animation and transcription
- Integrate and champion a video generation pipeline that looks and feels like a human interpreter
- Evaluate optimize and deploy computer vision models to production
- Collaborate with the data engineer to build scalable training and inference pipelines
- Automate and accelerate CV tasks for annotation and content generation
Requirements :
- PhD in Computer Science AI or related field or equivalent industry experience
- 3 years working with PyTorch and computer vision models
- Proven ability to take ML models from research to production
- Solid understanding of machine learning deep learning optimization and language models
- Experience working with motion or sign language data is a strong advantage
- Publication record in top-tier computer vision or ML venues preferred
- Strong Python skills and experience integrating models into cloud environments
Benefits:
Work on a fulfilling life-changing product (Literally)
Join as a key player at an early stage and receive generous options
Unlimited time off and sick days
Hybrid work model
Annual company get-together
Bring your pet to work
About Us:
Nagish makes communication accessible for people who are Deaf or hard of hearing.
Our team is passionate about making the world more accessible using our state-of-the-art tech - made for consumers and enterprises.
We are backed by some of the best investors out there: Comcast Techstars Vertex Precursor Contour Cardumen and more.
Remote Work :
Yes
Employment Type :
None
Employment Type
None
