
AI-Powered Innovation Leader
3 days ago
Elevate your career with our pioneering AI-Powered Customer Engagement Platform.
We seek a visionary Data/ML Engineer to bridge the gap between data engineering and machine learning. Design, build, and deploy scalable data pipelines and machine learning models that drive business growth and customer engagement.
Key Responsibilities:- Data Pipelines: Develop efficient data pipelines utilizing tools like Airflow or dbt.
- Machine Learning: Train ML models using Python libraries such as scikit-learn, LightGBM, and XGBoost to solve complex business problems, including churn prediction, upsell propensity, and lead scoring.
- Inference Services: Build real-time inference services to serve predictions into production systems, ensuring seamless integration with existing workflows.
- Retraining and Monitoring: Set up retraining and monitoring pipelines using tools like MLflow or similar, ensuring data quality, reproducibility, and compliance with regulatory requirements.
- Experience: 3-5+ years in data engineering or applied machine learning.
- Technical Skills: Strong proficiency in Python, SQL, and one or more ML libraries (scikit-learn, LightGBM, XGBoost). Experience with event-driven systems (Kafka, Redis, ClickHouse) and MLOps tools (MLflow, BentoML, Ray Serve) is a plus.
- Problem-Solving: Ability to design time-based labels, avoid data leakage, and demonstrate strong problem-solving skills in a fast-paced environment.
- MLOps experience with bandit algorithms, A/B testing, or uplift modeling.
- Prior work with customer engagement, CRM, or subscription businesses.
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