Description

You will operationalize machine learning models and integrate them into production environments.

This role is on-site.

Responsibilities

• Partner with Data Scientists and Engineers to deploy models and pipelines into on-premise and cloud production environments.
• Transform data science prototypes into production-ready code and automate model training, testing, and deployment via continuous delivery pipelines.
• Build data APIs and delivery services to support operational and analytical applications.
• Design and implement metrics to verify model effectiveness and optimize solutions for performance and scalability.
• Maintain model integrity through continuous training, retraining, and troubleshooting of production issues.

Required Skills

• 5+ years of experience in machine learning or related engineering roles.
• Proficiency with AI/ML platforms and frameworks including TensorFlow, Apache MXnet, Theano, Keras, CNTK, scikit-learn, H2O, or Spark MLlib.
• Experience with scalable data extraction tools such as Cassandra or MongoDB.
• Hands-on experience with version control systems like GIT (GitLab, Bitbucket, or similar).
• Proficiency using project management and tracking tools including JIRA and VersionOne.
• Ability to develop deep learning systems and automate ML continuous delivery pipelines.
• Experience building APIs to serve and consume models.

Preferred Skills

• Experience with on-premise infrastructure deployment.
• Background in data engineering or data science prototyping.

Key Skills

Education

Any Gradute