Jobs → Engineering → ML Engineer

About the Role We are seeking a Senior Machine Learning Engineer to join a centralized AI Engineering team responsible for designing, building, and supporting enterprise AI, machine learning, and generative AI solutions across the organization. This team enables a wide range of initiatives spanning traditional machine learning, generative AI, agentic AI, and enterprise-scale AI platforms. Key Responsibilities • Design and architect end-to-end AI, machine learning, and generative AI solutions within AWS cloud environments. • Build and deploy real-time and batch inference applications using services such as SageMaker, ECS, API Gateway, and related cloud technologies. • Develop enterprise-grade generative AI and agentic AI applications leveraging Gemini, Vertex AI, LLMs, RAG architectures, and orchestration frameworks. • Design and implement scalable feature store solutions supporting both real-time and batch machine learning workflows. • Build and maintain CI/CD pipelines, infrastructure-as-code deployments, model serving frameworks, and automated operational processes. • Develop integration patterns connecting AI applications to enterprise systems, APIs, data platforms, and business workflows. • Implement monitoring, observability, model performance tracking, and SLA management for production AI systems. • Optimize AI applications for scalability, reliability, latency, cost, and overall production performance. • Collaborate with Data Scientists to operationalize machine learning models and accelerate production deployment. • Provide technical leadership on architecture decisions, cloud service selection, and AI engineering best practices. Requirements • 10+ years of experience in machine learning engineering • Strong background in software engineering and cloud architecture • Experience with AWS AI Platform Architecture (SageMaker, ECS, API Gateway, Real-Time Inference, Infrastructure Design) • Experience with Generative AI Engineering (Gemini, Vertex AI, Agentic AI, RAG, LLM Application Development) • Experience with MLOps & Feature Platform Engineering (Feature Stores, Streaming Pipelines, CI/CD, Model Monitoring, Observability)