Description

Key Responsibilities
Translate business objectives and propensity-model use cases into a target-state solution architecture and phased implementation roadmap.
Design AWS architecture for data ingestion, storage, transformation, feature engineering, model training, batch and real-time scoring, and consumption of outputs.
Define integration patterns, APIs, workplace strategy, CI/CD approach, observability, resiliency, and disaster-recovery considerations.
Establish architectural guardrails for IAM, encryption, networking, data access, auditability, lineage, and responsible model use.
Guide technology selection and ensure designs meet performance, scalability, reliability, maintainability, and cost objectives.
Lead design reviews and provide technical direction to Data Scientists, ML Engineers, Data Analysts, and client engineering teams.
Own architecture documents, solution diagrams, interface specifications, non-functional requirements, and key technical decisions.
Identify architecture risks, dependencies, assumptions, and mitigations; support issue resolution through build and deployment.

Required Skills and Experience RequirementsAWS architecture: Robust hands-on design experience with S3, Glue, Athena, Redshift,



SageMaker, Lambda, IAM, Lake Formation, CloudWatch, EventBridge, and related AWS services.

Data and ML platforms: Data lake/lakehouse patterns, ETL/ELT, feature engineering, model lifecycle, batch and real-time inference, model registry, and monitoring.

Engineering: Python and SQL awareness, APIs, containerization, Git-based delivery, CI/CD, infrastructure-as-code concepts, and distributed systems.

Architecture practices: Security by design, high availability, scalability, integration architecture, performance engineering, governance, and cost optimization.

Leadership: Robust stakeholder management, workshop facilitation, decision-making, documentation, mentoring, and executive communication.

Preferred Qualifications
AWS Certified Solutions Architect certification or equivalent practical expertise.
Experience delivering customer analytics, propensity, churn, cross-sell, upsell, next-best-action, or recommendation solutions.
Experience in BFSI, insurance, or another regulated industry.
Exposure to explainable AI, model risk management, and responsible AI controls.

📌 Machine Learning Engineer Bengaluru
🏢 IITjobs
📍 Bengaluru