Description

You will design, implement, and deploy machine learning and deep learning models within production environments.

This role is on-site.

Responsibilities

• Build inferencing pipelines and manage the full ML/DL model lifecycle in coordination with data science and cloud engineering teams.
• Deploy models into production using MLOps best practices and contribute to automated test suites for continuous integration.
• Participate in code reviews to maintain high code quality standards.
• Build ETL pipelines using UC4 or Airflow.

Required Skills

• 3+ years of software development experience.
• Proficiency in Python, including Pandas and NumPy.
• Expertise in Deep Learning and Computer Vision.
• Experience with TensorFlow or PyTorch.
• Hands-on experience with GCP, AWS, or Azure cloud platforms.
• Experience scaling containerized applications using Docker and Kubernetes.
• Knowledge of Apache Spark, PySpark, and Kafka.
• Proficiency in SQL queries and RDBMS databases.
• Working knowledge of CI/CD tools like Jenkins and SonarQube.

Preferred Skills

• Experience with MLOps workflows and model governance.

Key Skills

Education

Any Graduate