Description

You will develop and deploy machine learning models to drive algorithmic decision-making and personalization in digital products.

This role is remote.

Responsibilities

• Develop and optimize predictive and prescriptive models using supervised and unsupervised learning techniques.
• Implement and fine-tune Large Language Models (LLMs) and Generative AI solutions for user engagement.
• Design and build scalable data pipelines for large-scale ETL processing using SQL and cloud solutions.
• Utilize MLOps practices to deploy, monitor, and maintain machine learning models in production.
• Collaborate with cross-functional teams in 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: 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 and LLMs.

Preferred Skills

• Any Graduate degree in a quantitative or technical field.

Key Skills

Education

Any Graduate