Description

You will drive the adoption of algorithmic decision-making by developing and deploying machine learning models to enhance personalization and automation in digital products.

Responsibilities

• Develop and optimize predictive and prescriptive models using supervised and unsupervised learning techniques.
• Utilize MLOps practices to efficiently deploy, monitor, and maintain machine learning models in production.
• Implement and fine-tune Large Language Models (LLMs) and Generative AI solutions for user engagement.
• Design and develop robust data pipelines for large-scale ETL processing using SQL and cloud solutions.
• Collaborate with cross-functional teams within an Agile/DevOps environment to drive data-driven innovation.

Required Skills

• 7+ years of experience in Data Science, Machine Learning, or related fields.
• Strong expertise in Python and SQL.
• Proficiency with modern ML frameworks, including TensorFlow, PyTorch, and SciKit-Learn.
• Experience with MLOps tools such as MLflow, Kubeflow, or Airflow.
• Proficiency in cloud platforms (AWS or GCP) and scalable data engineering.
• Strong understanding of probability theory, statistics, and experimental design (A/B Testing).
• Experience with collaborative software engineering practices (Agile, DevOps).
• Familiarity with ETL Processes.
• Experience with LLMs.

Key Skills

Education

Any Graduate