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Machine Learning Engineer

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Hybrid

Machine Learning Engineer

Quantiphi Analytics Solutions

Machine Learning Engineer

Skills

SQL QueriesPythonNumPypandasMachine LearningAIAWSKubernetes

2 months ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

20 August 2026

What they need


Quantiphi is an award-winning AI-first digital engineering company driven by the desire to solve transformational problems at the heart of business. Quantiphi solves the toughest and complex business problems by combining deep industry experience, disciplined cloud and data-engineering practices, and cutting-edge artificial intelligence research to achieve quantifiable business impact at unprecedented speed. We are passionate about our customers and obsessed with problem-solving to make products smarter, customer experiences frictionless, processes autonomous and businesses safer by detecting risks, threats and anomalies. Together with partners and customers, we embark on a data and AI led transformation journey that delivers impactful and measurable results.

Job Role Senior Machine Learning Engineer (3-4 yr)

As a Senior 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:

  • Machine Learning Engineer with 34 years of experience, based in Bangalore, with a requirement to work from the clients 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 below AWS Services -

  • Bedrock Agentcore

  • Sagemaker Studio, ECR, API Gateway

  • DynamoDB and MSK

  • Elastic Beanstalk

  • Glue and Lambda

  • ECS, 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)

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