
Chief Data and Machine Learning Architect
2 weeks ago
About Data and Machine Learning
We are seeking a highly skilled professional to bridge the gap between data engineering and machine learning.
The ideal candidate will have experience in designing and building data pipelines, training models, and deploying them into production at scale.
Responsibilities:- Data Pipelines: Design and build data pipelines to transform raw events into usable features.
- Label Computation: Define and compute labels from historical events.
- Machine Learning: Develop and train ML models using Python (scikit-learn, LightGBM, XGBoost).
- Inference Services: Build real-time inference services to serve predictions into production systems.
- Pipeline Monitoring: Set up retraining and monitoring pipelines (Airflow, MLflow).
- Integration: Collaborate with backend engineers to integrate model outputs into workflows.
- Data Quality: Ensure data quality, reproducibility, and compliance.
- 3–5+ years of experience in data engineering or applied ML.
- Strong proficiency in Python, SQL, and one or more ML libraries.
- Experience with data pipelines and event-driven systems.
- Understanding of ML lifecycle: training, serving, monitoring, retraining.
- Ability to design time-based labels.
- Strong problem-solving skills and eagerness to work in a dynamic environment.
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