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Open nowPosted 18 days ago

Senior Machine Learning Engineer - Traditional

Quantiphi83 open roles

Where
IN KA Bengaluru
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Your applicationOpen nowSenior Machine Learning Engineer - TraditionalQuantiphi · IN KA Bengaluru

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Quantiphi's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

8.3% of postings close within 7 days. Measured by our own scanner across the market. Quantiphi postings stay open a median of 29 days.

Share of postings closed within
  1. 1.9%1 day
  2. 3.9%3 days
  3. 8.3%7 days
  4. 15.3%14 days
  5. 34.2%30 days
This job: posted 18 days ago

Quantiphi median: 29 days open

The 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!

JOB ROLE - ML Engineer

As an ML Engineer This role focuses on predictive modeling development utilizing Jupyter Notebook environments alongside AWS cloud infrastructure services.

Must have Skills:

  • Must be capable of working independently with minimal supervision alongside the client's business/technical team
  • 4+ years experience in Traditional Machine Learning & Predictive Modeling: Hands-on experience building and fine-tuning ML models for regression/classification tasks, specifically sales forecasting or growth prediction using time-series and tabular data
  • Python & ML Libraries: Strong command of Python with libraries such as Scikit-learn, Pandas, NumPy, and Jupyter Notebooks for model development and output presentation.
  • Model Testing and evaluation
  • Feature Engineering & EDA
  • AWS Data Ecosystem: Working knowledge of AWS S3 and Amazon Redshift for data ingestion, storage, and retrieval in a cloud development environment
  • Data Preparation & Quality: Experience in data handling, missing values, duplicates, inconsistencies, and building unified analytical datasets from multiple sources

Good to have skills:

  • Store/Retail Domain Knowledge: Understanding of retail KPIs, store segmentation frameworks, and business cockpit/reporting concepts
  • Stakeholder Communication: Ability to present model outputs, performance metrics, and insights to non-technical business stakeholders during weekly review cadences

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

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