Description

Lead the end-to-end machine learning lifecycle from data preparation to production deployment.

This role is on-site.

Responsibilities

• Lead data curation, feature engineering, and exploratory data analysis to prepare datasets for model development.
• Implement scalable AI/ML models and MLOps pipelines to manage the full model lifecycle.
• Develop and maintain ETL processes and data transformation techniques.
• Collaborate with cross-functional teams to align AI solutions with business and data requirements.

Required Skills

• 3–6 years of software engineering experience, including at least 3 years focused on AI/ML and data engineering.
• Strong programming proficiency in Python or R.
• Hands-on experience with ML frameworks such as TensorFlow or PyTorch.
• Practical knowledge of MLOps tools like MLflow or Kubeflow.
• Experience with cloud platforms including AWS, Azure, or GCP.
• Proficiency in SQL and big data tools such as Spark or Databricks.
• Solid understanding of ETL processes and data curation.

Preferred Skills

• Proficiency in Dataiku or Databricks.
• Experience in model optimization and hyperparameter tuning.

Key Skills

Education

Any Graduate