Senior Machine Learning Engineer - Data Analytics
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Before you apply
LocationIN KA Bengaluru
Work modehybrid
SenioritySenior
Experience3–5 yrs
Company size1,001–5,000 people
PostedApr 6, 2026 · 7mo ago
Verified live2d ago
At a glanceSummarised by Seekless from the posting.
3-4 years of experience as a Machine Learning Engineer
Good exposure on Python (Pandas, Numpy, Matplotlib, Advanced Python Syntax)
Hands-on experience on OpenAI Framework
Hands-on experience in developing RAG pipeline, LLM Gen AI models, and Prompt Engineering
Hands-on experience in creating MCPs (Model Context Protocol)
Exposure to Agentic frameworks like LangGraph and LangChain
Exposure to Agentic framework (like AWS Bedrock AgentCore) is mandatory
Exposure on Data Analytics - Advanced SQL and Amazon Redshift, AWS Glue, Amazon DynamoDB, Amazon Managed Streaming for Apache Kafka
Exposure on AWS Services: Amazon Bedrock (AgentCore), Amazon SageMaker Studio, Amazon Elastic Container Registry, Amazon API Gateway, AWS Elastic Beanstalk, AWS Lambda, Amazon Elastic Container Service, Kubernetes
Hands-on GenAI Model Providers (OpenAI models, Anthropic models, Gemini Models)
Knowledge of ML Algorithms: Bagging and Boosting algorithms
AWS Bedrock Models
Redshift and SQL
ML Algorithms: Bagging and Boosting algorithms
Knowledge of Data Pipelines (GlueJobs)
Based in Bangalore
Skills
Python
Pandas
Numpy
Matplotlib
OpenAI
RAG
LLM
LangGraph
LangChain
AWS Bedrock AgentCore
Amazon Redshift
AWS Glue
Amazon DynamoDB
Amazon MSK
Amazon SageMaker Studio
Amazon ECR
Amazon API Gateway
AWS Elastic Beanstalk
AWS Lambda
Amazon ECS
Kubernetes
SQL
AWS Bedrock Models
GlueJobs
About the company
While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
Role : Senior Machine Learning Engineer - Data Analytics
Experience : 3-5 Years
Location : Bangalore (Hybrid)
Role & Responsibilities:
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Experimenting with range of models, evaluating model performance and model selection.
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Performing data cleaning, feature engineering, selection and evaluation.
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Implementing the data and model training pipelines on cloud using AWS services such as sagemaker, lambda functions, etc.
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Documentation for Model architecture and solutions
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Collaboration with cross-functional teams, including platform engineers, Machine learning engineers, software developers and business stakeholders, to ensure data solutions meet business needs.
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Adhering to project timelines
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Communicate with non-technical stakeholders to understand their data requirements and convey the benefits of data solutions, including migration strategies
Must have skills:
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Machine Learning Engineer with 3–4 years of experience, based in Bangalore, with a requirement to work from the client’s office 2 days a week.
•
Good exposure on Python (Pandas, Numpy, Matplotlib, Advance Python Syntax’s etc)
•
Hands on experience on OpenAI Framework, required to develop AI applications.
•
Handson experience in developing the RAG pipeline, LLM Gen AI models and Prompt Engineering.
•
Handover experience on creating the MCP’s (Model Context Protocol).
•
Exposure on Agentic frameworks like langgraph and langchain.
•
Exposure to the Agentic framework (like AWS Bedrock Agentcore) is mandatory.
•
Exposure on Data Analytics - Data Analytics, Advanced SQL and Amazon Redshift, AWS Glue, Amazon DynamoDB, Amazon Managed Streaming for Apache Kafka.
•
Exposure on below AWS Services - Amazon Bedrock (AgentCore), Amazon SageMaker Studio, Amazon Elastic Container Registry, Amazon API Gateway, AWS Elastic Beanstalk, AWS Lambda, Amazon Elastic Container Service, Kubernetes.
•
Hands-on GenAI Model Providers (example : OpenAI models, Anthropic models and Gemini Models).
•
ML Algos : Bagging and Boosting algorithms
Good to have skills:
•
AWS Bedrock Models
•
Redshift and SQL
•
ML Algos : Bagging and Boosting algorithms
•
Knowledge of Data Pipelines (GlueJobs)
If you like wild growth and working with happy, enthusiastic over-achievers, you’ll enjoy your career with us*!*