Staff Data Engineer ( Boston or Chicago )

About the role

The Staff Data Engineer (Platform) will play a crucial role in designing, implementing and architecting frameworks, systems and automation that support the development, deployment and observability of state-of-the-art large language models (LLMs) and generative AI solutions.

Responsibilities

• Design and implement processes, systems and automation to streamline the development and deployment of AI solutions.
• Architect robust, reliable solutions for specific AI applications using appropriate cloud-based and open source technologies.
• Design and automate data pipelines to deliver complex data products to power training and online inference of AI systems.
• Deploy ML models, LLMs and GenAI systems into production, ensuring reliability, efficiency, and scalability across cloud or hybrid environments.
• Build and maintain robust CI/CD pipelines tailored to ML model lifecycle management, ensuring a streamlined and agile deployment process.
• Monitor model performance, identify potential improvements, and integrate feedback loops for continuous learning and adaptation.
• Integrate models with chat interfaces and conversational platforms to create responsive, user-centric applications.
• Investigate and implement agent-based architectures that support conversational intelligence and interaction modeling.
• Collaborate with cross-functional teams to design AI-driven features that enhance user experience and interaction within chat interfaces.
• Work closely with data scientists, product managers, and engineers to ensure alignment on project goals, data requirements, and system constraints.
• Mentor junior engineers and provide guidance on best practices in ML model development, deployment, and maintenance.
• Create and maintain comprehensive documentation for model architectures, code implementations, data workflows, and deployment procedures to ensure reproducibility, transparency, and ease of collaboration.

Qualifications

• Minimum Qualifications: 5+ years of experience in platform engineering with a focus on data and ML systems.
• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.