Architect - Machine Learning Engineer

Quantiphi; Bengaluru; On-site; INR 3,500,000 - 5,000,000; Full time

Job summary

Quantiphi is seeking an Architect - Machine Learning Engineer to design and deploy advanced ML models on AWS, focusing on NLP, LLMs, and agentic AI capabilities. You will work across data science and engineering to deliver scalable AI solutions while optimizing performance and reliability.

Candidates should have 7+ years of hands-on experience with AWS ML services, NLP, and deep learning, and be adept at building robust, production-grade architectures that integrate with Lambda, Bedrock, and

Qualifications

• Must have 7+ years of hands-on experience implementing and developing cloud ML solutions on AWS.
• Hands-on experience with AWS Sagemaker and real-time/batch inference.
• Strong NLP expertise including tokenization, embeddings, parsing, and NER.
• Deep learning concepts: Transformers, BERT, attention mechanisms.
• Proficient in Python; familiarity with NLP libraries (Hugging Face, SpaCy, NLTK).
• Experience with LLM tooling, prompt templating, vector stores, and context management.
• Experience with agentic AI architectures using LangChain or Bedrock Agents.
• Deploy scalable AI solutions on AWS using Lambda, Bedrock, Step Functions, S3, API Gateway, and SageMaker.
• Fine-tuning large language models (LLMs), LLama2, and generative AI.
• Knowledge of model evaluation, hyperparameters, and interpretability for web app integration.
• Familiarity with orchestration tools (Airflow, StepFunctions, SageMaker Pipelines, Kubeflow).
• Experience building secure, scalable APIs and integrating third-party data sources.

Responsibilities

• Design and develop advanced ML models and algorithms to solve complex business problems.
• Architect, deploy, and optimize models on AWS infrastructure for scalability and reliability.
• Collaborate with cross-functional teams to implement agentic AI workflows and multi-model integration.

Skills

Cloud ML solutions on AWS

SageMaker

NLP

Transformers / BERT / Attention

Python

NLP libraries (Hugging Face, SpaCy, N)

LLM / Generative AI

LangChain / Bedrock Agents

AWS services (Lambda, Bedrock, Step Fn

Model Context Protocol (MCP)

Agentic AI architectures

Vector stores & context management

Model evaluation & optimization

Workflow orchestration (Airflow, StepF

Secure, scalable APIs

Tools

Hugging Face Transformers

SpaCy

NLTK

Stanford NLP

LangChain

Amazon Bedrock

OpenSearch

Pinecone

Elasticsearch

SageMaker Pipelines

Job description

Job Role : Architect - Machine Learning Engineer

As an Architect : Machine Learning Engineer at Quantiphi, you will be responsible for designing and developing advanced machine learning models and algorithms to solve complex business problems. You will work on optimizing and deploying these models on AWS infrastructure, ensuring scalability and reliability.

Must have skills:

• 7+ years of relevant hands-on technical experience implementing, and developing cloud ML solutions on AWS.
• Hands-on experience on AWS Machine Learning services. Proven experience using AWS Sagemaker leveraging different types of data sources, Training jobs, real-time and batch Inference, and Processing Jobs.
• Natural Language Processing
• Should have experience with Deep Learning Concepts - Transformers, BERT, Attention models
• Strong programming skills in Python and experience with NLP libraries such as Hugging Face Transformers, SpaCy, NLTK, or Stanford NLP
• Strong understanding of NLP concepts: tokenization, embeddings, syntactic and semantic parsing, named entity recognition, and coreference
• Agentic AI
• Design and implement agentic AI architectures using frameworks such as LangChain or Amazon Bedrock Agents, enabling autonomous task planning, decision-making, and multi-step reasoning.
• Architect and deploy scalable AI solutions on AWS, leveraging services like Lambda, Bedrock, Step Functions, S3, API Gateway, and SageMaker.
• Develop and maintain Model Context Protocol (MCP) implementations to manage state, context windows, memory, and prompt orchestration across distributed agent systems.
• Integrate agentic workflows with LLMs (Titan, Nova, Cohere, Claude, etc.) via Bedrock, ensuring high-availability and multi-model support
• Must have Hands-on experience fine-tuning large language models( LLM) and Generative AI (GAI), specifically LLama2.
• Familiarity with LLM tool use, prompt templating, vector stores (e.g., Opensearch, Pinecone, Elasticsearch, Bedrock KB), and context management.
• Model Evaluation & Optimization: Evaluate LLM's zero-shot and few-shot capabilities, fine-tuning hyperparameters, ensuring task generalization, and exploring model interpretability for robust web app integration.
• Experience with at least one of the workflow orchestration tools, Airflow, StepFunctions, SageMaker Pipelines, Kubeflow etc.
• Experience implementing secure, scalable APIs and integrating with 3rd-party data sources and tools
• Ability to collaborate with cross-functional teams such as Developers, QA, Project Managers, and other stakeholders to understand their requirements and implement solutions.

Good to have skills:

• Experience of working for customers/workloads in the Edtech domain with use cases.