Quantiphi

Senior Machine Learning Engineer - Data Analytics

IN KA Bengaluru

Open 6 months, first seen by us 180 days ago

Pay: Pay not listed
Work setting: Hybrid — work setting source
Experience : 3-5 Years Location : Bangalore (Hybrid) Role & Responsibilities:
Read the full posting
Employment: Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting

Experiment with models, evaluate performance and select the best one
Clean data and engineer and select features
Implement data and model training pipelines on AWS (SageMaker, Lambda)
Document model architecture and solutions
Work with cross-functional teams and non-technical stakeholders on data needs

From the employer’s posting

Experimenting with range of models, evaluating model performance and model selection.

Performing data cleaning, feature engineering, selection and evaluation.

Implementing the data and model training pipelines on cloud using AWS services such as sagemaker, lambda functions, etc.

Documentation for Model architecture and solutions

Communicate with non-technical stakeholders to understand their data requirements

Apply at Quantiphi

Posting record

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Open 6 monthsWe first saw this posting 180 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records: Live
First seen by us: May 8, 2026180 days ago
Recorded sightings: 228
Last seen by us: Nov 4, 2026
Employer says posted: Apr 6, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 180

Up longer than most. Similar jobs usually come down between day 6 and day 69.

From 4,296 similar postings that came down. Coming down is not always a hire.

Quantiphi is hiring

30 open jobs

Open jobs by the week we first saw them, last 12 weeks.

ML Engineer hiring has slowed
Takes jobs down at a usual pace
3% of open jobs were reposted

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Python
SQL
AWS
DynamoDB
Kafka
Kubernetes
Redshift
SageMaker
Matplotlib
NumPy
pandas

Where the posting names them

- 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.

- 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.

- AWS Bedrock Models - Redshift and SQL - ML Algos : Bagging and Boosting algorithms

- Performing data cleaning, feature engineering, selection and evaluation. - Implementing the data and model training pipelines on cloud using AWS services such as sagemaker, lambda functions, etc. - Documentation for Model architecture and solutions

- 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 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).

Good to have skills: - AWS Bedrock Models - Redshift and SQL

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025: $140,300
Expected change, 2025 to 2035: 21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

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:

Experimenting with range of models, evaluating model performance and model selection.
Performing data cleaning, feature engineering, selection and evaluation.
Implementing the data and model training pipelines on cloud using AWS services such as sagemaker, lambda functions, etc.
Documentation for Model architecture and solutions
Collaboration with cross-functional teams, including platform engineers, Machine learning engineers, software developers and business stakeholders, to ensure data solutions meet business needs.
Adhering to project timelines
Communicate with non-technical stakeholders to understand their data requirements and convey the benefits of data solutions, including migration strategies

Must have skills:

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!

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