As a Principal GenAI Engineer, you will lead the design, development, and deployment of a scalable AI platform. Your role will focus on MLOps, machine learning standardization, GPU and cloud platform setup, and data integrations. Working closely with cross-functional teams, you will ensure the scalability, reliability, and efficiency of GenAI solutions while driving innovation and best practices.

Requirements:

• Platform Development: Design and develop a high-performance, reliable AI platform.
• LLMOps/MLOps: Implement and optimize MLOps practices for streamlined model lifecycle management.
• Standardization: Establish best practices for machine learning model development, testing, and deployment.
• Infrastructure Setup: Manage GPU and cloud platforms to support AI workloads.
• Data Integration: Develop robust data pipelines for seamless access to diverse data sources.
• Collaboration: Work with data scientists, software engineers, and platform engineers on AI solutions.
• Innovation: Stay updated with the latest advancements in GenAI and machine learning.
• Mentorship: Provide technical guidance and mentorship to junior engineers.

Qualifications:

• Experience: 5-8 years in AI/ML engineering with a strong track record in AI projects.
• Technical Expertise: Proficiency in ML frameworks (TensorFlow, PyTorch), MLOps tools (MLflow, Kubeflow), and cloud platforms (AWS, Azure).
• GPU Expertise: Hands-on experience in GPU computing and AI workload optimization.
• Programming Skills: Proficiency in Python, Java, or C++.
• Data Engineering: Strong skills in data integration, ETL, and working with large datasets.
• Problem-Solving: Excellent analytical and creative problem-solving skills.
• Communication: Strong interpersonal and communication skills for collaborative teamwork.