212 Machine Learning Architect jobs in Hyderabad

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 : 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.