Machine Learning Architect
Required skills
- AWS
- Generative AI
- AI/ML
- Cloud-based AI solutions
- SageMaker
- Bedrock
- Lambda
- API Gateway
- DynamoDB
- ECS
Nice to have
- PoC
- Go-to-market AI solutions
Role summary
Seeking a highly skilled Technical Architect with 9-12 years of experience in AWS, Generative AI, AI/ML, and scalable production-level architectures. This remote role involves leading technical teams and designing end-to-end cloud-based AI solutions. Responsibilities include architecting AI/ML/GenAI applications, ensuring best practices in cloud deployment, security, and scalability, and collaborating with cross-functional teams and multiple clients. The ideal candidate will design and implement architectures on AWS, lead full lifecycle development of AI/ML/GenAI solutions, define MLOps/DataOps/DevOps best practices, and architect solutions using services like SageMaker, Bedrock, Lambda, and API Gateway. Expertise in LLMs, RAG, vector databases, serverless, and microservices is crucial. The role also requires team leadership, client engagement, and defining AI/ML/GenAI roadmaps.
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 ScalingOriginally posted on Himalayas
Similar roles
Principal Machine Learning Architect | Enterprise Agentic SearchAtlassian · Remote · Remote- Principal Machine Learning ArchitectMCG Health · Seattle, WA · Hybrid
- Director, Global Learning Architecture & ProgramsPublicis Groupe Holdings · New York, NY · Onsite
- Summer 2027 Learning Architecture and Design InternDivergent Technologies · Torrance, CA · Onsite
- Senior Manager, Services Portfolio & Learning ArchitectureTenableinc · Remote · Remote
- Senior Learning ArchitectCharlie Health · Remote · Remote
