AI-Driven Data Engineer

1 week ago

Kota, Rajasthan, India beBeeEngineering Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

Job Title: Machine Learning Pipeline Developer

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We're looking for a skilled professional to join our team as a Machine Learning Pipeline Developer. This role is crucial in bridging the gap between data engineering and applied machine learning, building pipelines, training models, and deploying them into production at scale.

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  • About Us:
  • We're evolving into an AI-native platform, where intelligent agents predict churn, upsell opportunities, and automate member engagement.
">Responsibilities
  • Data Pipelines: Design and build efficient data pipelines to transform raw events (visits, purchases, campaigns) into usable features.
  • Label Generation: Define and compute labels (e.g., churn, upsell, lead quality) from historical events.
  • Machine Learning Modeling: Develop and train ML models (e.g., churn prediction, upsell propensity, lead scoring) using Python (scikit-learn, LightGBM, XGBoost).
  • Inference Services: Build real-time inference services to serve predictions into production systems.
  • Retraining and Monitoring: Set up retraining and monitoring pipelines (Airflow, MLflow, or similar).
  • Integration: Collaborate with backend engineers to integrate model outputs into Gleantap workflows.
  • Data Quality: Ensure data quality, reproducibility, and compliance (HIPAA for healthcare customers).
">Requirements
  • Experience: 3–5+ years of experience in data engineering or applied ML.
  • Skills: Strong proficiency in Python, SQL, and one or more ML libraries (scikit-learn, LightGBM, XGBoost, PyTorch).
  • Data Pipelines: Experience with data pipelines (Airflow, dbt, or custom ETL).
  • Event-Driven Systems: Comfortable with event-driven systems (Kafka, Redis, ClickHouse or similar OLAP).
  • ML Lifecycle: Understanding of ML lifecycle: training, serving, monitoring, retraining.
  • Problem-Solving: Strong problem-solving skills and eagerness to work in a startup environment.
">Nice-to-Haves
  • MLOps Tools: MLOps tools (MLflow, BentoML, Ray Serve).
  • Bandit Algorithms: Experience with bandit algorithms, A/B testing, or uplift modeling.
  • Customer Engagement: Prior work with customer engagement, CRM, or subscription businesses.
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