Data Scientist - Generative AI/Computer Vision
Indexed description
As a Computer Vision Data Scientist at SSP, you will be designing and developing state-of-the-art Generative AI solutions that will help shape how customers shop online. Some example applications include Style-based recommendations, Virtual Try-on, and Outfit recommendations. Your work will directly impact our 100+ million users and ensure their happiness. If you are passionate about working with Computer Vision and Generative AI, this is your opportunity.
The majority of our team is located in Budapest, Hungary, but you'll be able to work remotely anywhere in the EU.
Requirements
We are looking for smart people with good communication skills who are hungry to tackle interesting challenges. If the responsibilities are attractive to you and you are passionate about developing novel models and improving on the state of the art, we would love to hear about you.
We are impressed if you...
- Have a Master’s or Ph.D. in Computer Science, Computer Engineering, Computer Vision, or a related field
- Have experience in state-of-the-art Generative AI technologies
- Have experience designing and implementing AI solutions using Python
- Are proficient in ML and CV toolkits, e.g., PyTorch, openCV
- Experience using cloud computing services
- Have experience transferring technology from research into a shipping product
- Are able to present your results to both technical and non-technical audiences
- Clearly explain problems, present solutions, and debate strategies in English to both technical and non-technical audiences
- Understand a business problem, then propose and weigh multiple solutions
- Collaborate effectively with Data Scientists, Engineers, and Product Team members
- Estimate and plan machine learning projects and coordinate with engineering team members
- Experience with A/B testing as a form of model evaluation
- Hands-on experience with PySpark and/or Databricks
- Experience handling unstructured text and/or NLP methodology
- Experience building tooling, scripts (e.g. bash, python, etc), or systems to support ML investigations, deployments, etc.
- Monitoring production model performance using automated dashboards or data visualization
- You are active on GitHub and have contributed to open-source projects
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