Machine Learning Engineer – Data and AI

• Design, develop, fine-tune, and deploy generative AI models into scalable production environment
• Build and maintain APIs and microservices using FastAPI to expose AI capabilities enterprise wide
• Collaborate with the AI Infrastructure team to architect robust LLM pipelines, including training workflows and retrieval-augmented generation (RAG) systems
• Integrate AI solutions into enterprise applications using secure, cloud-native architectures and best practices
• Ensure AI models are explainable, reliable, and compliant with regulatory and internal governance standards
• Continuously monitor and optimize model performance using evaluation frameworks, observability tools, and iterative fine-tuning

• 8+ years of IT industry experience
• Minimum 2+ years of hands-on AI development experience
• 3+ years of experience in Python programming
• Proficient in Python with practical experience in LLMs, embeddings, vector databases and RAG architecture.
• Demonstrated experience with generative AI models, including multimodal models
• Hands-on experience with Hands-on experience with cloud-native AI infrastructure, including Azure AI Foundry or AWS Bedrock, Open AI Models and AI model governance frameworks
• Bachelor's degree in Computer Science, AI, or a related field (or equivalent professional experience)

Preferred Experience:

• GPU-accelerated training and inference using NVIDIA technologies, including NIM and NeMo frameworks
• Optimize and scale AI models with NVIDIA NIM, and fine-tuning models with NeMo services
• Familiarity with AI agentic frameworks and deploying AI agents in production environments
• Deploy models with low latency and high throughput, using frameworks like vLLM and other GPU model deployment tools
• CI/CD pipelines for ML and Generative AI workflows, along with containerization and orchestration (Docker, Kubernetes)