Machine Learning Engineer

Job Title: Machine Learning Engineer Pricing Optimizer Development

Relevant Experience - 5 to 8 Years

Bangalore location - Hybrid Mode

Immediate Joiners only preferred

Role Overview

Key Responsibilities

• Refactor and enhance the existing optimization logic for speed, scalability, and modularity.
• Model price-volume relationships using elasticity inputs at SKU and brand levels.
• Develop optimization logic using constrained techniques (e.g., linear/quadratic programming).
• Integrate business rules and constraints such as price bounds, SKU/brand-level caps, and TDP limits.
• Enable scenario-based optimization with user-defined goals (e.g., maximize profit or volume).
• Support multi-brand optimization without interdependency between SKUs and brands.
• Collaborate with cross-functional teams to validate model behavior and outcomes.

Inputs You’ll Work With

• SKU-level data: volume, elasticity, profitability, TDP, and price bounds.
• Business rules: brand-level caps, SKU exclusions, optimization targets.

Deliverables

• Modular Python-based optimization engine.
• JSON-based input/output support for seamless integration.
• Logging and fallback mechanisms for infeasible constraints.
• Unit tests and validation with historical data.

Tech Stack & Skills

• Proficient in Python, especially NumPy, Pandas, SciPy or Pyomo/CVXOPT.
• Experience with constrained optimization techniques.
• (Preferred) Background in price optimization, demand modeling, or econometrics.