Related skills
python pandas databricks pytorch spark📋 Description
- Ensure ML/AI systems are served reliably in production with low latency.
- Build and maintain serving layer for ML/AI solutions (APIs, connectors, async execution).
- Establish monitoring and reliability with dashboards, alerts, KPIs, and data checks.
- Enable repeatable ML delivery via CI/CD, testing, releases, and rollback.
- Contribute to Architecture Decision Records with platform upgrade ideas for ML/AI.
🎯 Requirements
- 4–7 years in software engineering, with at least 3 years in ML Ops or Data Engineering in production.
- Design high-availability serving layers using APIs (FastAPI, gRPC) for fintech workloads.
- Understand the handshake between data science and engineering; models packaged and versioned.
- Expert AWS or similar, Kubernetes, Airflow/Prefect, Databricks/Spark.
- Experience with batching and model quantization to balance throughput and costs.
- Python ML: NumPy, Pandas, scikit-learn; PyTorch/TensorFlow; Spark/Databricks; SQL.
🎁 Benefits
- Work on a problem that matters in Colombia.
- Be part of something big from the ground up—own your impact.
- Unparalleled growth opportunity in fintech.
- Join a world-class, global team.
- Competitive compensation and meaningful ownership.
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