Machine Learning Engineer

Essential functions

• Design and develop machine learning models focused on time series forecasting and predictive analytics.

• Engineer features and build pipelines to support scalable model training and evaluation.

• Collaborate closely with cross-functional teams to integrate AI models into production environments.

• Contribute to the development of a proactive recommendation engine powered by expert knowledge.

• Leverage cloud platforms to deploy, monitor, and optimize ML solutions.

Qualifications

• Proficiency in Python for machine learning and data processing tasks

• Hands-on experience with time series predictive modeling and feature engineering for temporal data

• Strong understanding of classical machine learning algorithms

• Experience working with cloud platforms (AWS, Azure, or GCP)

• Familiarity with ML model lifecycle including training, evaluation, and deployment

Would be a plus

• Experience in the demand forecasting domain or similar predictive analytics applications

• Knowledge of ensemble learning techniques and model performance optimization

• Familiarity with CI/CD pipelines for machine learning workflows

• Hands-on experience with model deployment and monitoring in production environments

• Background in Operations Research, including Linear Programming, Mixed Integer Programming, or other optimization techniques

We offer

• Work on bleeding-edge projects on a team of experienced and motivated engineers

• Flexible working hours

• Specialization courses

• 24 days annual leave + an additional of 5 sick days

• Floating Holidays

• Private medical subscription for employees and their family members

• Benefits basket with the total value of 650 euro/year

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.