About the Role
- - - - What the Candidate Will Do ----
- Design, develop, and productionize machine learning (ML) solutions in : Search and Discovery , GenAI, QU/Ranking , MOO optimizations.
- Productionize and deploy these models for real-world applications.
- Design and analyze experiments using a combination of data analysis/statistical analysis to lead the team to a reasonable inference.
- Review code and designs of teammates, providing constructive feedback.
- Collaborate with Product and cross-functional teams to brainstorm new solutions and iterate on the product.
- - - - Basic Qualifications ----
- Bachelor's or Master's in Computer Science, Statistics, or a related field.
- Experience with a strong focus on machine learning and optimization.
- Experience with ML packages such as Tensorflow, PyTorch, JAX, and Scikit-Learn.
- Solid understanding of statistical analysis and feature engineering techniques.
- Excellent communication and collaboration skills.
- Ability to work independently and take ownership of projects.
- Experience using SQL in a production environment.
- Experience in experimental design and analysis, exploratory data analysis, and statistical analysis.
- Experience with dashboarding and using data visualization tools.
- Experience using statistical methodologies such as sampling, statistical estimates, descriptive statistics, or similar.
- - - - Preferred Qualifications ----
- Experience in the Search and Recommendations Field.
- Experience in Query Understanding / Ranking or solving customer problems with NLP.
- Experience developing end-to-end GenAI products
For San Francisco, CA-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.
For Seattle, WA-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.