QX Impact - Machine Learning Engineer

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 data.

Responsibilities

• 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.
  
  

• 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.
  
  

• 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 effectively.
  
  

• 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.
  
  

• 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.