AI/ML Architect

About the Company

Responsibilities

• ● About Sutherland Artificial Intelligence. Automation.Cloud engineering. Advanced analytics.For business leaders, these are key factors of success. For us, they're our core expertise. We work with iconic brands worldwide. We bring them a unique value proposition through market-leading technology and business process excellence. We've created over 200 unique inventions under several patents across AI and other critical technologies. Leveraging our advanced products and platforms, we drive digital transformation, optimize critical business operations, reinvent experiences, and pioneer new solutions, all provided through a seamless "as a service" model. For each company, we provide new keys for their businesses, the people they work with, and the customers they serve. We tailor proven and rapid formulas, to fit their unique DNA.We bring together human expertise and artificial intelligence to develop digital chemistry. This unlocks new possibilities, transformative outcomes and enduring relationships. Sutherland Unlocking digital performance. Delivering measurable results.
• ● Required Skills & Experience: Overall experience: 10+ Years 6+ years of professional experience in machine learning, data science, or applied AI, with 3+ years in an architect or technical lead capacity. Strong hands-on coding proficiency in Python with production ML framework experience. Demonstrated experience taking models from prototype to production, not limited to POC or research work. Proven ability to conduct code reviews across ML pipelines, data engineering, and model deployment. Hands-on experience with classical ML techniques including supervised learning, anomaly detection, time-series analysis, and imbalanced classification. Working knowledge of MLOps tooling and production model lifecycle management. Cloud platform experience (Azure, AWS, or GCP) including ML services and deployment infrastructure. Proficiency with SQL and large-scale data processing. Familiarity with version control systems (Git, SVN, etc.). Strong problem-solving skills and ability to work independently. Preferred Skills: Experience with predictive maintenance, hardware failure prediction, or IoT/telemetry data. Exposure to log analytics, observability data, or large-scale unstructured data processing. Experience with Databricks, Spark, or similar distributed data platforms. Knowledge of REST API integration for model serving and inference endpoints. Client-facing consulting or services delivery background. Advanced degree (MS or PhD) in Computer Science, Statistics, Applied Mathematics, or related field. Experience in agile development environments.