AI role · Open offer

ML Engineer — commerce ranking

Flipkart

Full-time
Senior
Personalization
Hybrid
Embassy Tech Village, Bangalore, KA 560103, India · Hybrid
Bangalore, India
INR 35–60 LPA + ESOPs

This listing is optimized for AI-native talent: clear skills and tools so candidates know if they fit before they apply—and so you spend less time screening mismatches.

4 skills2 tools

At a glance

How you'll work, where, and key listing dates.

Employment: Full-time
Workplace: Hybrid
Location: Embassy Tech Village, Bangalore, KA 560103, India · Hybrid
Compensation: INR 35–60 LPA + ESOPs
Experience level: Senior
Team: Personalization
Benefits & perks

About this role

What the team is looking for and how this position fits.

Flipkart is hiring a Senior ML Engineer — commerce ranking on the Personalization team (Hybrid · Bangalore, India). This is a hands-on role in search & recommendations—not a generic “AI enthusiast” post.

You will own ranking, retrieval, and online experimentation end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.

Flipkart (Walmart) is India's largest e-commerce platform — ML center in Bangalore Embassy Tech Village.

ML Engineer: personalization, pricing, and search with Indian market seasonality.

Missions

Large-scale A/B culture on ranking and reco.
Cost-aware inference for mobile-first users.

Stack & environment

Python, PyTorch, Spark, Kubernetes.

What we look for

5+ years ML prod; hybrid Bangalore.

Skills we're hiring for

What each capability means for this role—not a keyword checklist.

Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
PyTorch
Training and inference with PyTorch: reproducible experiments, checkpointing, and deployment-minded exports.
SQL

Tools & stack

Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).

KubernetesTool
Deploying and scaling model services with health checks, autoscaling, and rollout discipline.
SparkTool
Distributed feature generation and batch scoring on large tabular or event datasets.

You're a strong fit if…

Tailored to this listing—use it as a self-check before you apply.

You can show evidence in your application: Ranking, reco, or pricing ML with A/B proof at Indian scale.
Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, SQL, Machine Learning, and Kubernetes.
You have owned ranking, retrieval, and online experimentation in production: debugging live issues, running postmortems, and iterating from real user or business signals.
You are comfortable with the hybrid rhythm (Hybrid · Bangalore, India)—onsite collaboration when it matters, deep work when remote.
You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.
You read the full listing (comp: INR 35–60 LPA + ESOPs, benefits in At a glance) and your expectations align.

Apply

Candidate accounts only: add your headline and bio on , and optionally a CV link or PDF so recruiters see your full résumé. Then write a short pitch below—applications use your login email.

What the employer asked for

Ranking, reco, or pricing ML with A/B proof at Indian scale.

Register, add a headline and bio, then you can attach a CV link or PDF on My account before you apply. That keeps applications tied to your profile and makes it easier for employers to review your background.

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