Job Summary :
We are seeking an experienced Machine Learning Specialist to join our team. The successful candidate will have a strong background in data engineering and applied machine learning, with expertise in building pipelines, training models, and deploying them into production at scale.
Key Responsibilities :
- Data Pipeline Development : Design and build data pipelines to transform raw events into usable features.
- Label Definition : Define and compute labels from historical events.
- Model Training : 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 or similar).
- Collaboration : Collaborate with backend engineers to integrate model outputs into 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.