Description

You will design, implement, and deploy machine learning and deep learning models within production environments. You will collaborate with Data Scientists and cloud engineers to build inferencing pipelines and manage the full ML/DL model lifecycle.

Responsibilities

• Design and implement technical solutions in coordination with data science and dependent teams.
• Deploy models into production using MLOps best practices.
• Participate in code reviews to maintain high code quality standards.
• Contribute to automated test suites to support continuous integration.
• Build ETL pipelines using UC4 or Airflow.

Required Skills

• 3+ years of software development experience.
• Proficiency in Python and libraries 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