Job Description: AI Engineer
Position Overview
We are seeking a talented AI Engineer to drive the end-to-end development of AI solutions across on-premises cloud environments. This role involves hands-on coding, building deploying AI models, developing AI agents portals, optimizing performance across GPU infrastructures. The engineer will apply best practices in software engineering, AI Ops, SDLC to deliver scalable, reliable, innovative AI services.
Key Responsibilities
• AI Solution Development
o Design, code, implement AI use cases that address business needs.
o Develop maintain AI agents, portals, models.
o Build optimize communication protocols fseamless integration across systems.
• Model Training & Deployment
o Train, fine-tune, evaluate AI/ML models using open-source enterprise frameworks.
o Deploy models in both on-premises cloud environments.
o Apply AI Ops practices to monitor, maintain, improve model performance.
• Performance Optimization & GPU Management
o Evaluate moniton-premises GPU usage to ensure efficient resource allocation.
o Optimize AI model performance through tuning, scaling, hardware utilization strategies.
o Apply best practices to scale out infrastructure by integrating new GPUs with existing GPU clusters.
• Engineering Practices
o Apply SDLC principles to AI solution development, ensuring quality maintainability.
o Follow best practices in coding, testing, documentation.
o Collaborate with cross-functional teams to integrate AI solutions enterprise systems.
• Continuous Improvement
o Stay updated with emerging AI technologies open-source platforms.
o Contribute to the evolution of AI development standards practices.
o Provide technical input to improve scalability, security, efficiency of AI services.
Qualifications
• Bachelor’s Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, related field.
• 3–7 years of experience in AI/ML development engineering.
• Strong coding skills in Python, Java, similar languages.
• Hands-on experience with open-source AI platforms (e.g., TensorFlow, PyTorch, Hugging Face).
• Familiarity with SDLC methodologies AI Ops practices.
• Experience with cloud platforms (Azure, AWS, GCP) on-premises infrastructure.
• Knowledge of communication protocols (REST, gRPC, WebSockets, etc.).
• Experience in GPU resource management, performance optimization, scaling strategies.
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