Machine Learning Engineer

T7E Aftermarket Connect Pvt Ltd; Mumbai; On-site; INR 1,000,000 - 2,000,000; Full time

Benefits offered by this job

Direct access to real trade data

Equity conversation possible for right profiles

Job summary

T7E Aftermarket Connect Pvt Ltd is seeking a Machine Learning Engineer to be the architect of their intelligence layer. The role involves building models to predict behavior, personalize engagement, and drive outcomes within trade ecosystems.

Key responsibilities include creating recommendation models, demand forecasting pipelines, and communicating outputs to non-technical stakeholders. Candidates should have 3-6 years of hands-on experience and proficiency in Python and SQL. The position is based in Mumbai, with exciting growth prospects in a profitable company.

Qualifications

• 3–6 years of hands-on ML engineering experience with deployed production models.
• Strong background in e-commerce or loyalty platforms where ML drove outcomes.
• Ability to communicate model outputs to non-technical stakeholders.

Responsibilities

• Build recommendation and propensity models for personalized loyalty offers.
• Develop demand forecasting and redemption prediction pipelines.
• Create dashboards and APIs to surface ML outputs for various teams.

Skills

Machine Learning Engineering

Python

SQL

REST APIs

E-commerce

Tools

TensorFlow

PyTorch

MLflow

Airflow

Job description

ABOUT THE ROLE

T7E Aftermarket Connect is building a Trade Growth Engine — an intelligent, data‑driven platform that powers loyalty, rewards, and channel activation for leading brands across Auto Aftermarket, Building & Construction, and Agriculture. As our Machine Learning Engineer, you will be the architect of the intelligence layer: building models that predict behaviour, personalise engagement, and drive measurable outcomes for our clients’ trade ecosystems. This is a founding ML role with direct visibility to the COO and CEO.

WHAT YOU WILL BUILD

• Recommendation and propensity models that drive personalised loyalty offers and mechanic/retailer engagement nudges
• Demand forecasting and redemption prediction pipelines for our rewards fulfilment engine
• Churn prediction and re‑engagement scoring across 200K+ trade partner profiles
• Segmentation and clustering models to enable targeted campaign execution for brand clients
• Dashboards and APIs that surface ML outputs to product, ops, and client‑facing teams
• Data pipelines and feature stores to ensure clean, consistent ML‑ready data across platforms

WHAT WE ARE LOOKING FOR

• 3–6 years of hands‑on ML engineering experience — not just research, but deployed, production models
• Strong background in e‑commerce, loyalty, fintech, or consumer platforms where ML drove business outcomes
• Proficiency in Python (scikit‑learn, XGBoost, TensorFlow or PyTorch), SQL, and REST APIs
• Experience building recommendation systems, propensity models, or NLP‑driven personalisation
• Comfort working with messy, real‑world transactional data — field ops, POS, scan logs, redemption records
• Ability to communicate model outputs to non‑technical stakeholders — client teams, ops, and leadership
• Based in or willing to relocate to the Central Line / Navi Mumbai / Thane corridor (office: Mulund West)

GOOD TO HAVE

• Experience with MLOps tooling — MLflow, Airflow, Docker, or cloud ML platforms (AWS SageMaker / GCP Vertex)
• Exposure to GenAI or LLM‑based applications (RAG, fine‑tuning, prompt engineering)
• Prior work in trade marketing, channel loyalty, or distribution ecosystem analytics
• Knowledge of Marathi or Hindi — helpful for understanding field data context

TECH ENVIRONMENT

• Python
• SQL / MySQL
• REST APIs
• Node.js stack

WHY T7E

• 12-year-old profitable company scaling from ₹20 Cr to ₹100 Cr — ML is central to that journey, not a side experiment
• Direct access to real trade data: scan logs, loyalty transactions, FSO field activity across 5+ marquee clients
• Lean, senior team — you will own the ML charter end to end, not be a cog in a large data science org
• SME IPO on the horizon — early equity conversation possible for the right profile
• Clients include ENI, Castrol, Gulf, Akzo Nobel, Michelin, Pidilite, SKF — real industry depth

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