Machine Learning Engineer

Essential functions

• Execute data infrastructure requests from Data Science teams.

• Execute machine learning (ML) infrastructure requests from Data Science teams.

• Support Data Science teams responsible for customer modeling and store modeling.

Qualifications

• Experience in data engineering and/or ML engineering in the cloud

• Azure experience, especially ADLS, Azure ML

• Experience in feature engineering, feature selection

• Experience with Hadoop and Spark

• Knowledge of MLops best practices, e.g. model lifecycle, evaluation deployment, monitoring

• Solid knowledge of Data Science essentials, e.g. classic machine learning, evaluation metrics, feature engineering, and feature selection

Would be a plus

• Snowflake experience

• Spanish language

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office

About us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.