478 Machine Learning Architect jobs in Bengaluru

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 overall experience of 9-12 years.This role involves architecting AI/ML/Gen AI-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 Sage Maker, Bedrock, Lambda, API Gateway, Dynamo DB, ECS, S3, Open Search, and Step Functions.Lead full lifecycle development of AI/ML/Gen AI solutions—from Po C to production—ensuring reliability and performance.Define and implement best practices for MLOps, Data Ops, and Dev Ops 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 Sage Maker 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/Gen AI-driven solutions.Conduct technical workshops, training sessions, and knowledge-sharing initiatives.Multi-Client & Business StrategyManage multiple client engagements, delivering AI/ML/Gen AI solutions tailored to their business needs.Define AI/ML/Gen AI 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 & TechnologiesCloud & Dev OpsAWS Services: Bedrock, Sage Maker, Lambda, API Gateway, Dynamo DB, S3, ECS, Fargate, Open Search, RDSMLOps: Sage Maker Pipelines, CI/CD (Code Pipeline, Git Hub Actions, Terraform, CDK)Security: IAM, VPC, Cloud Trail, Guard Duty, KMS, CognitoAI/ML & Gen AILLMs & Generative AI: Bedrock (Claude, Mistral, Titan), Open AI, LlamaML Frameworks: Tensor Flow, Py Torch, Lang Chain, Hugging FaceVector DBs: Open Search, Pinecone, FAISSRAG Pipelines, Prompt Engineering, Fine-tuningSoftware Architecture & ScalabilityServerless & Microservices ArchitectureAPI Design & Graph QLEvent-Driven Systems (SNS, SQS, Event Bridge, 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

• 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 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

• 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 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

• 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 Scali

Role : Associate Architect - Machine Learning (Gen AI)

Experience : 6 to 8 Years

Location : Bangalore / Mumbai (Hybrid)

Job Summary:

We are looking for an experienced Associate Architect - Machine Learning to join our team, focused on building Agentic AI workflows, fine-tuning Large Language Models (LLMs), performing prompt engineering, and applying related generative AI techniques. The ideal candidate will have expertise in cutting-edge AI technologies and the ability to design, develop, and deploy AI solutions that can autonomously perform tasks with minimal human intervention.

Roles and Responsibilities:

• Agentic AI Development : Design, develop, and optimize domain adaptive agentic AI systems that helps in automating business processes
• LLM Fine-Tuning : Work with large-scale pre-trained models (like Llama, Mistral etc.) to fine-tune with techniques like PEFT, SFT and adapt them for specific applications and domains. Evaluate and Optimize for performance, accuracy, and efficiency.
• Prompt Engineering : Design prompts with techniques like Chain of Thought, Few Shot to enhance model responses, ensuring that model outputs are aligned with use case requirements.
• AI Workflow Automation : Build end-to-end workflows for AI solutions, from data collection and preprocessing to training, deployment, and continuous improvement in production environments.
• Collaboration with Cross-functional Teams : Work closely with data scientists, software engineers, and product managers to define AI product requirements and deliver innovative solutions.
• Research & Development : Stay current with the latest research and developments in generative AI, deep learning, NLP, reinforcement learning, and related fields to ensure that the organization stays at the forefront of technology.
• Scaling and Deployment : Deploy machine learning models at scale, optimizing for latency, throughput, and robustness in production environments.
• Documentation & Reporting : Maintain clear documentation of models, workflows, and experiments, and communicate results effectively to stakeholders.

Skill Set Required:

Experience :

• Minimum 5+ years of hands-on experience in machine learning and AI engineering.
• Proven track record in working with LLMs such as Llama, Mistral and models like GPT, BERT, T5, or similar.
• Expertise in designing, fine-tuning, and deploying generative AI models and building agentic workflows.
• Strong experience in prompt engineering to optimize AI models performance.

Technical Skills :

• Proficiency in Python, TensorFlow, PyTorch, or other ML frameworks.
• Proficiency in building agentic workflows with tools like Langgraph, CrewAI, Autogen, PhiData or similar.
• Familiarity with cloud platforms (AWS, GCP, Azure) for deployment and scaling of models.
• Experience with NLP tasks, such as text classification, text generation, summarization, and question answering.
• Knowledge of reinforcement learning, multi-agent systems, or other autonomous decision-making frameworks.
• Familiarity with SDLC life cycle , data processing tools (e.g., Pandas, NumPy, etc.) and version control (e.g., Git).

Soft Skills :

• Strong problem-solving and analytical skills.
• Excellent communication and teamwork abilities to collaborate with stakeholders.
• Ability to work independently and drive projects to completion with minimal supervision.

Preferred Skills & Qualifications:

• Experience in deploying AI models at scale in production environments.
• Expertise in large-scale data processing, optimization techniques, and model deployment.

Role: Technical Architect - ML

Location: Mumbai/Bangalore

Experience: 10-15 years

Role & Responsibilities

• Act as a trusted technical advisor for customers, addressing complex technical challenges pertaining to AI/ML Opportunities
• Provide expertise in the architecture, design, and development of solutions within AWS
• Collaborate with internal teams and external stakeholders to design optimized solutions on AWS Cloud
• Work with the pre-sales team on RFP, RFIs and help them solutioning for different AI/ML use cases
• Strong analytical skills to evaluate scenarios and use cases, offering potential solutions for AI/ML implementations
• Stay up-to-date with the latest advancements in Generative AI and Machine Learning
• Demonstrated problem solving, communication, and organizational skills, a positive attitude, and the proven ability to negotiate and influence others to obtain desired results.
• Ability to speak in business terms, as well as the ability to effectively communicate both internally and externally.
• Ability to collaborate with cross-functional teams such as Developers, QA, Project Managers, and other stakeholders to understand their requirements and implement solutions.
• Ability to communicate technical roadmap, challenges, and mitigation.

Required Skills

• Experience: 8+ years
• Well-versed with AWS Cloud and AWS Machine Learning capabilities and offerings:

-Proven experience using AWS Sagemaker leveraging different types of data sources,

-Training jobs, real-time and batch Inference, and Processing Jobs.

• Hands-on experience of working with Sagemaker studio, canvas, and data wrangler.
• Experience with at least one of the workflow orchestration tools, Airflow, StepFunctions, SageMaker Pipelines, Kubeflow etc.
• Ability to collaborate with cross-functional teams such as Developers, QA, Project Managers, and other stakeholders to understand their requirements and implement solutions.
• Ability to create end to end solution architecture for model training, deployment and retraining using native AWS services such as Sagemaker, Lambda functions, etc.
• Knowledge of a variety of machine learning techniques (Supervised/unsupervised etc.) (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
• Understanding of LLM architectures ( LLaMA, Claude, Amazon Nova etc.), with a focus on their training and inference workflows
• Expertise in designing, fine-tuning, and deploying generative AI models and building agentic workflows.
• Experience with prompt engineering and optimization techniques to improve LLM outputs for specific business use cases
• Good Understanding of open-source LLM frameworks and libraries (e.g., Hugging Face Transformers, LangChain, LlamaIndex, Haystack)
• Great analytical skills, with expertise in analytical toolkits such as Logistic Regression, Cluster Analysis, Factor Analysis, Multivariate Regression, Statistical modeling, predictive analysis
• Experience in leveraging AWS Lambda/API Gateway services for AI/ML model consumption and inferences. Hands-on experience with Dev Ops(CICD) & ML Ops services/tools.
• Must have led teams of ML Engineers in end-to-end production deployment for projects.
• Strong understanding of data privacy, compliance, and responsible AI practices while building and deploying LLM solutions in production environments