Senior Machine Learning Engineer

Location: Mumbai, Maharashtra, India

Department: Weekday's Client via platform

Workplace: on_site

Employment Type: full

Description

This role is for one of Weekday’s clients

Min Experience: 5+ years
Location: Mumbai, Maharashtra, India
JobType: full-time

This is a model-building role, not an ML platform or MLOps role. You'll be designing the statistical and machine learning models that sit at the core of our sports intelligence products — predictive models over live match data, and player and team performance metrics that are published, sold, and argued about by people who know the sport well.

Requirements

Responsibilities:

- Design, build, and validate predictive and descriptive models over live and historical sports data
- Define performance metrics and rating systems, and defend their methodology to product, commercial, and external stakeholders
- Own feature engineering and the analytical datasets your models depend on, working from the team's data marts
- Establish validation, backtesting, and monitoring practices appropriate to models whose outputs are published in real time
- Take models from prototype to production, working with data and backend engineers on serving and integration
- Investigate model failures and drift, and improve accuracy and robustness over time
- Translate domain questions from product and sports stakeholders into tractable modelling problems

Requirements:

- 5+ years building statistical or machine learning models in production, with clear ownership of modelling decisions rather than only implementation
- Strong grounding in applied statistics: probabilistic modelling, regression, time-series or sequential data, and rigorous validation
- Strong Python and the standard modelling stack; strong SQL
- Demonstrated ability to work with large, messy, real-world event data
- Ability to explain and defend a model's methodology to a non-technical audience — a substantial part of this role is making a number credible, not just accurate
- Judgement about model complexity: knowing when a simple, explainable model is the correct answer

Must-have skills

Python, SQL