Roles and Responsibilities

• Collaborate with data scientists and data engineers to productionalize AI/ML models.
• Implement, optimize, and deploy AI/ML models in both On-Prem (e.g., Cloudera Hadoop) and Cloud (e.g., AWS, GCP) environments.
• Work with PySpark and Python to build scalable data pipelines and integrate with ML workflows.
• Deploy AI/ML models using container orchestration tools like OpenShift and Kubernetes.
• Monitor, troubleshoot, and enhance AI/ML models post-deployment based on user feedback and performance metrics.
• Support ML Ops/LLM Ops processes, ensuring automation, versioning, and reproducibility of ML models.
• Optimize system performance, ensure high availability, and maintain observability of ML services.
• Stay current with emerging trends in AI/ML and contribute ideas for continuous improvement.

Required Qualifications

• Strong programming experience in Python and PySpark.
• Proven ability to work with AI/ML models in production environments.
• Solid understanding of ML Ops practices and tools.
• Experience working with Big Data platforms such as Cloudera Hadoop.
• Proficiency in deploying workloads in Cloud platforms (AWS, GCP).
• Experience with container orchestration and microservices architecture using OpenShift/Kubernetes.
• Understanding of large language models (LLMs) and their implementation considerations.
• Excellent problem-solving and analytical skills.
• Strong communication skills and ability to collaborate across cross-functional teams.

Posted By