Machine Learning Engineer

Job Title- Machine Learning Engineer

Location: Mohali / Chandigarh | Full-time | Work from Office

We’re looking for a Machine Learning Engineer to work at the intersection of data, AI, and customer platforms , enabling smarter decision-making and impactful customer experiences.

What You Bring

✅ Bachelor’s degree in Computer Science / Data Science / Engineering (Master’s preferred)

✅ 5+ years of hands-on experience in Machine Learning Engineering

✅ Strong foundation in ML algorithms, model building, and deployment

✅ Expertise in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, XGBoost

✅ Experience working with large-scale data platforms (Treasure Data CDP preferred)

✅ Hands-on experience with customer segmentation, recommendation systems, predictive modeling, and real-time decisioning

✅ Exposure to cloud-based ML frameworks & deployment (MLflow, Kubeflow, SageMaker, etc.)

✅ Excellent SQL skills (Presto, MongoDB, MySQL, BigQuery)

✅ Experience with A/B testing and marketing experimentation frameworks

✅ Knowledge of NLP, deep learning, or advanced recommendation systems for customer behavior analysis

✅ Ability to translate business problems into ML-driven solutions

✅ Experience in customer-facing environments (CRM, marketing automation platforms)

Your Impact

1️⃣ ML Model Development & Implementation

• Design, develop, and deploy machine learning models within the CDP to enhance customer insights, segmentation, and personalization

• Build models for churn prediction, customer behavior analysis, recommendations, and CLV modeling

• Implement supervised & unsupervised learning techniques including classification, regression, clustering, and deep learning

2️⃣ Model Evaluation, Monitoring & Optimization

• Continuously evaluate and improve ML model performance for accuracy and business impact

• Set up monitoring systems to track production models and detect data drift or performance issues

• Optimize models for scalability, efficiency, and cost within the CDP ecosystem

3️⃣ Scalability & Performance Optimization

• Ensure ML workflows scale efficiently to handle large volumes of customer data in real-time or near real-time

• Optimize data pipelines and ML models for low latency, high throughput, and fast insights

4️⃣ Research & Continuous Learning

• Stay updated with the latest trends in Machine Learning, AI, and CDP technologies

• Evaluate new algorithms, tools, and techniques to enhance the overall ML and CDP capabilities