Data Scientist (Computer Vision) – Kazakhstan
Our AI Customer Support and Safety team is working on many areas including Computer Vision, NLP, RL etc, bringing business value to our products and improving the lives of our customers. Now we are aiming to strengthen several streams and looking for an experienced middle Data Science engineer, who will help us in our journey. The primary focus for this position will be automation of the driver verification process, for which experience in computer vision is essential.
- Perform EDA and data pre/processing, generate features, build ML training pipelines
- Organize processes for data discovery, annotation data processing, define and improve metrics, automate models training
- Prepare models and pipelines for production
- Monitor and maintain deployed models
- Share your knowledge, findings and experience on internal and external events
- Strong technical/math background (calculus, statistics, probabilities, etc.)
- Main ML algorithms and metrics are a must
- Production experience in training computer vision models
- Awareness of modern ML technologies, including LLMs, but it’s not the only thing you have experience with
- Python and development experience are a strong plus, including ML model lifecycle management and ML-based service deployment
- Knowledge/experience in using other languages and a Software Engineering background are a plus
- Ability to balance quality and speed depending on the case, and justify your decision
- Ability to explain the background and consequences of your technical decisions to non-technical stakeholders, including product and business managers
- English and Russian communication skills
- Help us challenge injustice by creating fair choices for millions of people across 1100+ cities in 48 countries.
- Develop your professional skills with access to mentoring, career consulting, and learning programs.
- Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program.
- Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects.
- Work alongside people who take initiative, speak openly, and challenge themselves to grow.
- Improve your language skills through co-financed courses and internal speaking clubs.
