AI / ML Engineer (Generative AI)

We are seeking a highly skilled and experienced Senior Machine Learning Engineer to join our dynamic team. In the rapidly evolving world of Generative AI (GenAI), this role demands not only traditional machine learning expertise but also a deep understanding of GenAI-specific challenges. The ideal candidate will be a pivotal bridge between the theoretical capabilities of GenAI models and their practical application in production environments, ensuring our GenAI solutions are innovative, reliable, scalable, secure, and cost-effective., * Deploy, monitor, and maintain GenAI models in production, ensuring reliable performance in real-world settings

• Build and maintain efficient data pipelines and storage solutions that support model operations
• Utilize cloud platforms (AWS, Azure, GCP) for model deployment, containerization (Docker), orchestration (Kubernetes), and infrastructure as code (Terraform/CloudFormation)
• Develop CI/CD pipelines, manage version control (Git), and automate deployment processes
• Implement secure coding practices, authentication, authorization, and robust monitoring and alerting for infrastructure and model performance
• Apply deep expertise in LLMs, GenAI architectures, frameworks like Hugging Face, prompt engineering, and specialized GenAI infrastructure
• Apply advanced techniques such as Retrieval-Augmented Generation (RAG), hallucination monitoring, and human-in-the-loop systems
• Design and develop agent and multi-agent systems using frameworks like LangChain, enabling interaction with external APIs and tools
• Implement strategies to manage and reduce operational costs associated with GenAI deployments

This is a right-to-hire position requiring permanent U.S. work authorization Sponsorship is not available. Recent MS or PhD graduates are encouraged to apply., * Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field; Master’s degree preferred

• 5+ years of experience as a machine learning engineer deploying models in production
• Strong proficiency in Python and software engineering principles
• Solid understanding of machine learning fundamentals and model lifecycle management
• Experience with cloud platforms, containerization, and infrastructure management
• Familiarity with DevOps practices and automation tools
• Expertise in GenAI frameworks, prompt engineering, and model serving
• Ability to manage GPU/TPU resources and optimize model serving frameworks
• Experience developing agentic systems and multi-agent architectures
• Proven track record of cost optimization in AI deployments
• Comfortable working in a fast-paced environment as an independent contributor