About Us

The QX Impact was launched with a mission to make A.I accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them. Secondly, without insights businesses won't be able to deliver differentiated products/services; and finally, without insights, businesses cant achieve a new level of Operational Excellence is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.

Role Overview

We are seeking a Machine Learning Engineer to lead the end-to-end development of production-grade analytical applications. This is a high-impact role requiring a blend of deep statistical modeling and machine learning. You will be responsible transforming raw consolidated data into high-accuracy forecasts through advanced feature engineering, rigorous model selection, and statistical validation.

This role is for an engineer who thrives in the research-to-code transition, ensuring that every model is mathematically sound, resistant to overfitting, and optimized for high-dimensional manufacturing Feature Engineering & Discovery: Design and build complex feature sets for diverse problem types, including behavioural features for churn, sensor-based lags for maintenance, and seasonal encodings for demand forecasting.

Model Selection & Optimization: Conduct systematic experimentation across diverse algorithms (e.g., XGBoost, LightGBM, Prophet, or Deep Learning) to identify the best-performing models.
Model Training & Testing: Develop, train, tune, and test a variety of ML architectures including time-series, classification and regression.
Statistical Validation & Evaluation: Define and track complex evaluation metrics tailored to manufacturing, such as MAPE, RMSE, etc., while performing deep-dive bias-variance analysis.
EDA & Research: Perform exploratory data analysis on consolidated Gold layer data to uncover hidden drivers of business outcomes and identify correlations between external signals.
Refinement & Performance Tuning: Address critical modeling challenges including bias-variance tradeoffs, class imbalance, and overfitting to ensure models generalize to real-world production data.

Skills & Requirements

3+ Years of Experience: Proven track record of developing and delivering production-grade ML models across multiple domains (Sales, Finance, Manufacturing, or Supply Chain).
Mastery of the Python Ecosystem: Expert-level skills in Pandas, NumPy, Scikit-learn, and SciPy.
Advanced Algorithmic Knowledge: Deep expertise in supervised and unsupervised learning, specifically ensemble methods (Boosting/Bagging) and time-series frameworks.
Statistical Foundations: Strong grasp of hypothesis testing, probability distributions, and the mathematical principles behind model evaluation and optimization.
SQL Proficiency: Expert ability to manipulate data within consolidated database layers to create the Silver feature sets required for training.
Education: Bachelors or Masters degree in a quantitative field (e.g., Data Science, Statistics, Mathematics, or Computer Science).
Cloud Awareness: Experience with Azure Machine Learning or similar cloud modelling environments.
Engineering Familiarity: Basic understanding of Docker, MLflow, or FastAPI for handing models off to deployment teams.

Personal Attributes

Strong problem-solving skills with a passion for data architecture.
Excellent communication skills with the ability to explain complex data concepts to non-technical stakeholders.
Highly collaborative, capable of working with cross-functional teams.
Ability to thrive in a fast-paced, agile environment while managing multiple priorities Tech Savvy: Anticipating and adopting innovations in business-building digital and technology applications.
Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels.
Action Oriented: Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
Customer Focus: Building strong customer relationships and delivering customer-centric solutions.
Optimize Work Processes: Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.

Why Join Us

Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
Work on impactful projects that make a difference across industries.
Opportunities for professional growth and continuous learning.
Competitive salary and benefits package.

Application Details

Ready to make an impact Apply today and become part of the QX Impact team!

(ref:hirist.tech)

QX Impact - Machine Learning Engineer - Python