Nilasu Consulting Services Pvt Ltd logo

ML Architect(NCS/Job/ 1549)

For Ai Services And Consulting Company

9 - 12 Years

Full Time

Up to 15 Days

Up to 50 LPA

1 Position(s)

Remote/Work From Home (Wfh)

9 - 12 Years

Full Time

Up to 15 Days

Up to 50 LPA

1 Position(s)

Remote/Work From Home (Wfh)

Job Description

PFB JD For your reference. 

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

  • Design 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 Management

  • 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.

Team & Client Engagement

  • 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.
  •  
  • Multi-Client & Business Strategy
  •  
  • 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.

 

Key Skills & Technologies

 

Cloud & DevOps

  • 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

AI/ML & GenAI

  • 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
  • Software Architecture & Scalability
  • Serverless & Microservices Architecture
  • API Design & GraphQL
  • Event-Driven Systems (SNS, SQS, EventBridge, Step Functions)
  • Performance Optimization & Auto Scaling

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