Technical Architect leading design and deployment of data science applications in cloud environments. Requires expertise in software engineering, MLOps, and collaboration across teams.
Responsibilities
Architect scalable, reusable data science and machine learning pipelines leveraging cloud services such as AWS SageMaker, Textract, and Comprehend.
Design multi-tenant systems with robust application deployment architectures and rate-limiting mechanisms to ensure high availability and performance.
Translate custom client requirements into scalable technical architecture, conducting impact assessments and delivery planning.
Lead development and deployment of complex data science and information extraction solutions in client cloud environments.
Manage and optimize CI/CD pipelines for continuous delivery of data science applications.
Own the tenant onboarding process and manage lifecycle operations for multi-tenant deployments.
Oversee DevOps and MLOps teams to ensure reliable, consistent releases and maintenance of deployed products.
Drive collaboration between engineering, data science, delivery, and leadership teams to align technical solutions with business goals.
Act as a key technical advisor during client engagements, translating technical complexities into clear business value propositions.
Requirements
Bachelor’s degree in computer science, Information Technology, Business Administration, or related field.
7+ years of experience spanning software engineering, data science, and DevOps roles.
Proven expertise in cloud platforms (AWS preferred), MLOps, and CI/CD pipeline design and management.
Strong programming skills and hands-on experience with data science application development and deployment.
Experience managing multi-tenant SaaS or ML platforms.
Strong leadership, communication, and stakeholder management skills.
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