Senior Machine Learning Architect

October 29

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Description

• The Sr. ML Architect is expected to work closely with other stakeholders (ML Engineers, Data Scientists, and Data Engineers) with key responsibilities to: • Develop an in-depth understanding of the current Risk Analytics landscape and lead the Future State Architecture for the new Risk Platform in GCP. • Lead evaluation of design options, tools, and utilities to build implementation patterns for MLOps using SAS Viya and VertexAI in the most optimal ways. • Create solutions and conduct hands-on PoCs to move Risk Platform Components (KBS, CRIF, and SAS) to GCP. • Work with Suppliers, Google Professional Services, and other Consultants as required to migrate key Risk models to GCP for Lending and Insurance platforms • Collaborate with program managers to plan iterations, backlogs, and dependencies across all workstreams to progress the program at the required pace. • Led a team of ML Architects to guide Design/Architecture/Tool/Implementation Patterns, Troubleshooting Guidance, and Remove Roadblocks for the Engineering teams. • Drive adoption of standardized architecture, design, and quality assurance approaches across all workstreams and ensure migrated solutions adhere to established standards • Provide advisory and technical consulting across all initiatives including product evaluations and recommendations, security, architecture assessments, integration considerations, etc. • Collaborate with Data Engineering architects, SMEs, and technical leads to establish best practices for data products needed for model training and monitoring considering regulatory policy and legal compliance.

Requirements

• Bachelor’s degree in computer science or related field • 10+ years of relevant work experience in solution, application, and data architecture, with deep understanding of cloud hosting concepts and implementations. • 5+ years of hands-on experience in Risk Analytics, MLOps and Architecting Solutions for ML based models and Rules Engines • Experience in migrating legacy applications to Cloud platform and business adoption of these platforms • Knowledge of enterprise frameworks and technologies. Strong in architecture design patterns, experience with secure interoperability standards and methods, architecture tools and processes. • Strong understanding on DevOps principles and practices, including continuous integration and deployment (CI/CD), automated testing & deployment pipelines. • Good understanding of cloud security best practices and be familiar with different security tools and techniques like Identity and Access Management (IAM), Encryption, Network Security, etc. • Understanding of microservices architecture • Ability to negotiate & influence key stakeholders • Strong leadership, communication, interpersonal, organizing, and problem-solving skills.

Benefits

• Immediate medical, dental, vision and prescription drug coverage • Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more • Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more • Vehicle discount program for employees and family members and management leases • Tuition assistance • Established and active employee resource groups • Paid time off for individual and team community service • A generous schedule of paid holidays, including the week between Christmas and New Year’s Day • Paid time off and the option to purchase additional vacation time.