Sr. Machine Learning Solutions Architect

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.

• Lead end-to-end architecture, design, and delivery of machine learning and data platform solutions for enterprise clients, ensuring scalability, security, and measurable business value.
• Translate business requirements and data science needs into production-ready MLOps architectures, including model training, deployment, monitoring, and retraining pipelines.
• Design and implement secure, scalable environments for data ingestion, transformation, and model development across cloud and hybrid ecosystems.
• Build and optimize data pipelines and distributed processing systems using modern big data technologies such as Spark, Snowflake, and Databricks.
• Define and enforce best practices for model lifecycle management, including CI/CD for ML, observability, testing strategies, and operational reliability.
• Collaborate closely with cross-functional teams and client stakeholders to guide technical strategy, architecture decisions, and solution roadmaps.
• Contribute to internal accelerators, reference architectures, and reusable frameworks that improve delivery efficiency and standardization across engagements.

Requirements

• 8+ years of experience in machine learning engineering, data engineering, or software engineering with production-grade ML system delivery.
• Strong expertise in Python (or similar languages such as Scala or Java), including experience building APIs and backend services using frameworks like Flask or Django.
• Hands-on experience with distributed data processing and big data platforms such as Spark, Snowflake, Databricks, Redshift, or EMR.
• Strong knowledge of cloud and systems architecture across AWS, Azure, or GCP, including storage, networking, and data infrastructure design.
• Proven experience deploying machine learning models into production environments with robust monitoring, testing, and operational support.
• Advanced SQL skills, including query optimization and working with large-scale distributed datasets.
• Experience in consulting or client-facing delivery environments, with the ability to translate technical concepts into business value.
• Strong communication and leadership skills with the ability to guide cross-functional teams and influence technical direction.

Benefits

• Remote-first work environment across the United States
• Competitive compensation package with performance-based opportunities
• 401(k) plan with company match
• Comprehensive medical, dental, and vision insurance
• Paid time off including approximately 4 weeks PTO and 10 holidays
• Annual learning and development stipend
• Home office equipment support
• Career growth opportunities through complex, high-impact enterprise AI projects
• Collaborative, global, and values-driven engineering culture