AI Systems Designer

3 days ago

pushkar, India beBeeArtificialIntelligenceEngineer Full time

Job DescriptionWe are seeking a highly skilled AI engineer with expertise in designing, building, and deploying AI systems using modern AWS-native tooling.The ideal candidate will have strong hands-on experience across the AWS AI/ML ecosystem, including SageMaker, Bedrock, Lambda, EC2, ECR, and Step Functions.Key Responsibilities:Machine Learning Model Development: Build, deploy, and optimize machine learning models on AWS using SageMaker, Bedrock, Lambda, EC2, ECR, and Step Functions.End-to-End ML Pipelines: Develop end-to-end ML pipelines (training, evaluation, deployment, monitoring) for scalable, production-grade solutions.Vector Search and Embeddings: Implement vector search, embeddings pipelines, and LLM-based applications using Amazon Bedrock or open-source models.RAG Workflows: Build RAG (Retrieval-Augmented Generation) workflows using AWS services such as OpenSearch / Aurora / DynamoDB.Data Engineering & MLOps:Data Pipelines: Build scalable data pipelines using Glue, EMR, Kinesis, or Lambda.MLOps Workflows: Implement MLOps workflows using SageMaker Pipelines, Model Registry, MLflow (if applicable), and CI/CD.Model Performance Monitoring: Monitor and optimize model performance, drift detection, retraining triggers.Backend & Integration:Model Integration: Integrate models with applications via REST APIs / async APIs.Microservices: Work with microservices using Python (FastAPI), Node.js, or similar.Inference Endpoints: Build inference endpoints optimized for low latency and cost efficiency.Cloud Architecture & Optimization:AWS Well-Architected Framework: Architect and deploy AI workloads following AWS Well-Architected best practices.Compute Optimization: Optimize compute, storage, and networking for high performance and cost efficiency.Security and Compliance: Implement security, IAM policies, data encryption, and compliance practices.

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