Machine Learning ArchitectgoML • Davanagere, IN
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Machine Learning Architect
goML • Davanagere, IN
30+ days ago
Job descriptionDesign 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. Architect 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. Lead 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. Manage 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. AWS Services : Bedrock, SageMaker, Lambda, API Gateway, DynamoDB, S3, ECS, Fargate, OpenSearch, RDS MLOps : SageMaker Pipelines, CI / CD (CodePipeline, GitHub Actions, Terraform, CDK) Security : IAM, VPC, CloudTrail, GuardDuty, KMS, Cognito LLMs & Generative AI : Bedrock (Claude, Mistral, Titan), OpenAI, Llama ML Frameworks : TensorFlow, PyTorch, LangChain, Hugging Face Vector DBs : OpenSearch, Pinecone, FAISS RAG Pipelines, Prompt Engineering, Fine-tuning Serverless & Microservices Architecture API Design & GraphQL Event-Driven Systems (SNS, SQS, EventBridge, Step Functions) Performance Optimization & Auto Scali
Job Summary
We 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 overall experience 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 Responsibilities
Technical Leadership & Architecture
- Design 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 Expertise
Cloud & Infrastructure Management
Team & Client Engagement
Multi-Client & Business Strategy
Key Skills & Technologies
Cloud & DevOps
AI / ML & GenAI
Software Architecture & Scalability
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Machine Learning Architect • Davanagere, IN
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