Data Scientist-Computer Vision Specialist
il y a 4 semaines
Mirakl, a leading platform economy company, is seeking a highly skilled Data Scientist-Computer Vision to join our team. As a Data Scientist-Computer Vision, you will be responsible for prototyping, iterating, and deploying algorithms in collaboration with our Product, Data Engineering, and Development teams.
Key Responsibilities- Develop and implement computer vision algorithms to extract product attributes from images, generate new backgrounds for products, and moderate products based on their images.
- Work on detecting product variants and categorizing products using multimodal approaches.
- Collaborate with our Data Engineering and Development teams to deploy and monitor the performance of these algorithms.
- 3+ years of experience as a Data Scientist with a strong background in computer vision and machine learning.
- Proven experience in developing and deploying machine learning models in a production environment.
- Strong knowledge of computer vision algorithms, including NLP, and state-of-the-art architectures such as transformers.
- Experience with Spark development is a plus.
- Pragmatic, data-driven, and business-oriented mindset.
- Ability to work independently and take ownership of projects.
- Excellent communication and collaboration skills.
- Opportunity to work on impactful projects that will be deployed on over 500 e-commerce/marketplaces in 40 countries.
- State-of-the-art techniques and tools, including multimodal models and vision transformers.
- Autonomy and responsibility in project ownership.
- Flexible work arrangements, including freelance or CDI options.
We use a range of technologies and tools to deliver our solutions, including Spark, Python, and cloud-based services.
What You'll Enjoy- Collaborative and dynamic work environment.
- Opportunities for professional growth and development.
- Flexible work arrangements and benefits.
Mirakl is committed to diversity, equity, and inclusion. We welcome applications from candidates of all backgrounds and perspectives.
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