Description

You will develop and deploy machine learning solutions to drive business insights.

This role is on-site.

Responsibilities

• Develop and optimize predictive and prescriptive models using supervised and unsupervised learning.
• Utilize MLOps and GCP services to deploy, monitor, and maintain ML models in production.
• Implement and fine-tune Large Language Models (LLMs) and Generative AI solutions for automation.
• Design data pipelines for large-scale ETL processing and collaborate with data engineering teams.
• Communicate complex methodologies and business insights to technical and non-technical audiences.

Required Skills

• 5+ years of experience in Data Science or Machine Learning.
• Strong expertise in Python and SQL.
• Proficiency with ML frameworks including TensorFlow, PyTorch, and SciKit-Learn.
• Experience with MLOps tools such as MLflow, Kubeflow, or Airflow.
• Proficiency in cloud platforms, specifically GCP.
• Strong understanding of statistics, probability theory, and A/B Testing.
• Experience implementing and testing recommendation engines.
• Familiarity with Agile and DevOps software engineering practices.
• Bachelor's or Master's degree in a quantitative field.

Key Skills

Education

Bachelor's or Master's degrees