
Sr. Machine Learning Solutions Architect
Job Description
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Sr. Machine Learning Solutions Architect in United States.
In this role, you will act as a senior technical leader responsible for designing and delivering production-grade machine learning and data solutions for enterprise clients across diverse industries. You will translate complex business and data science requirements into scalable, cloud-native architectures that enable reliable model deployment, monitoring, and lifecycle management. Working in a highly collaborative consulting environment, you will partner with data scientists, engineers, DevOps teams, and business stakeholders to turn data into actionable, production-ready AI systems. This position blends deep technical expertise with client-facing leadership, requiring both architectural vision and hands-on execution. You will play a key role in shaping MLOps standards, improving delivery frameworks, and advancing best practices across modern data platforms. The environment is fast-paced, remote-first, and centered on ownership, autonomy, and measurable business impact.
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Sr. Machine Learning Solutions Architect in United States.
In this role, you will act as a senior technical leader responsible for designing and delivering production-grade machine learning and data solutions for enterprise clients across diverse industries. You will translate complex business and data science requirements into scalable, cloud-native architectures that enable reliable model deployment, monitoring, and lifecycle management. Working in a highly collaborative consulting environment, you will partner with data scientists, engineers, DevOps teams, and business stakeholders to turn data into actionable, production-ready AI systems. This position blends deep technical expertise with client-facing leadership, requiring both architectural vision and hands-on execution. You will play a key role in shaping MLOps standards, improving delivery frameworks, and advancing best practices across modern data platforms. The environment is fast-paced, remote-first, and centered on ownership, autonomy, and measurable business impact.