Fullstack AI Engineer
2 days ago
Responsibilities
- Build ML models: recommendation, clustering, prediction.
- Analyze user behavior and event log data.
- Develop quick prototypes (CLI, dashboards, lightweight web apps).
- Build and optimize REST APIs for model inference.
- Integrate ML models into production backend systems.
- Develop batch/real-time inference pipelines.
- Design and maintain ETL/ELT data pipelines.
- Process large datasets (sessions, metadata, streaming data).
- Deploy services and models using Docker and cloud platforms (GCP/AWS).
- Monitor model performance and backend service health.
Requirements
- 2–3 years experience in ML, Backend, or Data Engineering.
- Strong Python (NumPy, Pandas, scikit-learn).
- Basic familiarity with PyTorch/TensorFlow.
- Experience building simple recommendation or clustering models.
- Strong SQL (PostgreSQL/BigQuery).
- Experience with ETL/ELT and data cleaning.
- Experience building APIs or FastAPI/Flask).
- Familiarity with Docker and basic CI/CD.
- Understanding of system design fundamentals and caching.
- Knowledge of embeddings, vector databases, or LLM integration (nice to have).
Contract PKWT (WFO)
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