Senior ML Engineer

GameDistrict is seeking a Senior Machine Learning Engineer to join their team in Lahore, Pakistan. This on-site role requires 4 to 5+ years of experience in data science or machine learning, with a strong track record of deploying models into production. The successful candidate will be responsible for developing predictive models that enhance player engagement and improve game experiences. Working closely with product, marketing, and engineering teams, you will manage projects end-to-end—from problem definition and data exploration to model deployment and impact analysis—across a portfolio of mobile games.

Key Responsibilities

- Design, develop, and maintain predictive models focused on player behavior and engagement using large-scale event and telemetry data.
- Translate business challenges into machine learning problems and collaborate with stakeholders to define success metrics.
- Engineer robust features from complex datasets to improve model performance.
- Build and manage production pipelines for training, scoring, monitoring, and retraining machine learning models.
- Design and analyze experiments, including A/B tests, to evaluate the impact of model-driven decisions on business outcomes.
- Communicate technical findings and recommendations effectively to both technical teams and non-technical stakeholders.
- Mentor junior engineers by reviewing code and models, and contribute to establishing best practices in machine learning development and deployment.

Required Qualifications

- 4 to 5+ years of practical experience in data science or machine learning engineering, with at least two models successfully deployed in production environments.
- Proven expertise in user-level predictive modeling techniques such as classification, regression, and time-to-event analysis.
- Strong proficiency in Python, including libraries such as Pandas, NumPy, and Scikit-learn, along with advanced SQL skills for handling large datasets.
- Deep understanding of gradient-boosted tree algorithms (XGBoost, LightGBM, CatBoost) and solid knowledge of statistics and probabilistic modeling.
- Experience with model evaluation techniques, including calibration, handling class imbalance, avoiding data leakage, and validation using time-based splits.
- Familiarity with ML deployment and MLOps practices, including containerization, workflow orchestration, experiment tracking, and model monitoring.
- Working knowledge of experimentation methodologies, including A/B test design, statistical significance, and causal inference methods.
- Ability to clearly explain complex technical results and their business implications to diverse audiences.
- Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field, or equivalent professional experience.

Preferred Qualifications

- Experience in mobile gaming or consumer-facing applications.
- Knowledge of real-time feature stores and low-latency model serving architectures.
- Exposure to deep learning techniques for sequential or behavioral data analysis.
- Experience working with distributed processing frameworks such as Apache Spark.
- Contributions to the data science community through publications, Kaggle competitions, or open-source projects.

This role offers the opportunity to work at the intersection of gaming and advanced machine learning, driving impactful insights that shape player experiences. If you have a passion for data-driven decision-making and enjoy collaborating across teams to deliver scalable ML solutions, this position provides a dynamic environment to grow your expertise.