Machine Learning Architect
我们正在寻找一个高技能技术建筑师，拥有 AWS,生成人工智能，AI/ML 以及可扩展的生产级架构方面的专业知识。理想的候选人应该有经验处理多个客户，领导技术团队和设计端到端基于云 AI 解决方案。这项职位包括构建 AI/ML/GenAI 驱动应用程序，确保与跨功能团队合作时在云部署，安全性和可扩展性方面最佳实践。关键责任技术领导力 & 建筑设计并为 AI / ML 应用程序实现可扩展，安全和高性能架构。使用 AWS 服务如 SageMaker,Bedrock,Lambda,API Gateway,DynamoDB,ECS,S3,OpenSearch 和 Step Functions 等多租户企业级 AI/ML 解决方案的架构者。领导 AI/ML/GenAI 解决方案的完整生命周期开发从 PoC 到生产确保可靠性和性能。定义并实施 AWS 上 MLOps, DataOps 和 DevOps 的最佳实践.AI/ML & Generative AI ExpertiseDesign 对话式 AI,RAG （恢复增强代）和使用模特如 Claude (Anthropic),Mistral,Llama 和 Titan AI 的生成人工智能架构。优化 LLM 推断线路，嵌入式，矢量搜索以及基于 AI 的应用程序的混合检索策略.Drive ML 模型训练，部署和监测使用 AWS SageMaker 和/ML 管道管理.Cloud & InfrastructureArchitect 为事件管理，无服务器和微服务架构。确保云部署的高可用性，灾难恢复和成本优化。实施 IAM,VPC,安全最佳实践和合规性。团队与客户参与率领导并指导 ML 工程师，Python 开发人员和云工程师组成的团队。与业务利益相关者，产品团队以及多个客户合作定义需求并提供 AI/ML/GenAI 驱动的解决方案。开展技术研讨会，培训会议和知识共享计划。多客户和商业战略管理多个客戶的接触，为他们的业务需求提供定制的 AI/ML / GenAI 解决方案。定义 AI/ML (AI) /Gen (AI) 路线图，证明概念策略和进入市场 保持最新的 AI 进步和推动人工智能/ML 产品创新。需求关键技能 &技术 Cloud & DevOpsAWS 服务：Bedrock,SageMaker,Lambda,API 门户端，DynamoDB,S3
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This is a remote position.
Job SummaryWe are looking for a highly skilled Technical Architect with expertise in AWS, Generative AI, AI/ML, and scalable production-level architectures. The ideal candidate should have experience handling multiple clients, leading technical teams, and designing end-to-end cloud-based AI solutions with an overallexperience of 9-12 years.This role involves architecting AI/ML/GenAI-driven applications, ensuring best practices in cloud deployment, security, and scalability while collaborating with cross-functional teams.Key ResponsibilitiesTechnical Leadership & ArchitectureDesign and implement scalable, secure, and high-performance architectures on AWS for AI/ML applications.Architect multi-tenant, enterprise-grade AI/ML solutions using AWS services like SageMaker, Bedrock, Lambda, API Gateway, DynamoDB, ECS, S3, OpenSearch, and Step Functions.Lead full lifecycle development of AI/ML/GenAI solutions—from PoC to production—ensuring reliability and performance.Define and implement best practices for MLOps, DataOps, and DevOps on AWS.AI/ML & Generative AI ExpertiseDesign Conversational AI, RAG (Retrieval-Augmented Generation), and Generative AI architectures using models like Claude (Anthropic), Mistral, Llama, and Titan.Optimize LLM inference pipelines, embeddings, vector search, and hybrid retrieval strategies for AI-based applications.Drive ML model training, deployment, and monitoring using AWS SageMaker and AI/ML pipelines.Cloud & Infrastructure ManagementArchitect event-driven, serverless, and microservices architectures for AI/ML applications.Ensure high availability, disaster recovery, and cost optimization in cloud deployments.Implement IAM, VPC, security best practices, and compliance.Team & Client EngagementLead and mentor a team of ML engineers, Python Developer and Cloud Engineers.Collaborate with business stakeholders, product teams, and multiple clients to define requirements and deliver AI/ML/GenAI-driven solutions.Conduct technical workshops, training sessions, and knowledge-sharing initiatives.Multi-Client & Business StrategyManage multiple client engagements, delivering AI/ML/GenAI solutions tailored to their business needs.Define AI/ML/GenAI roadmaps, proof-of-concept strategies, and go-to-market AI solutions.Stay updated on cutting-edge AI advancements and drive innovation in AI/ML offerings.
Requirements
Key Skills & TechnologiesCloud & DevOpsAWS Services: Bedrock, SageMaker, Lambda, API Gateway, DynamoDB, S3, ECS, Fargate, OpenSearch, RDSMLOps: SageMaker Pipelines, CI/CD (CodePipeline, GitHub Actions, Terraform, CDK)Security: IAM, VPC, CloudTrail, GuardDuty, KMS, CognitoAI/ML & GenAILLMs & Generative AI: Bedrock (Claude, Mistral, Titan), OpenAI, LlamaML Frameworks: TensorFlow, PyTorch, LangChain, Hugging FaceVector DBs: OpenSearch, Pinecone, FAISSRAG Pipelines, Prompt Engineering, Fine-tuningSoftware Architecture & ScalabilityServerless & Microservices ArchitectureAPI Design & GraphQLEvent-Driven Systems (SNS, SQS, EventBridge, Step Functions)Performance Optimization & Auto Scaling
Originally posted on Himalayas