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Job details
Addi is a leading financial platform building the future of payments, shopping, and banking in Colombia.
They are looking for a Machine Learning Engineer to build a world-class ML Ops foundation to accelerate the transition from model prototype to production.
The successful candidate will have 4-7 years of experience in software engineering, with at least 3 years focused on ML Ops or Data Engineering in a production environment.
Requirements
Proven experience in architecting and serving production-grade ML systems4–7 years of experience in software engineering, with at least 3 years focused specifically on ML Ops or Data Engineering in a production environmentExpert-level knowledge of AWS (or similar), Kubernetes, Airflow/Prefect, and Databricks/SparkTrack record of implementing request batching and model quantization to balance high-performance throughput with infrastructure costsExpert-level knowledge of core ML libraries (NumPy, Pandas, scikit-learn) and at least one deep learning framework (PyTorch or TensorFlow)Solid expertise in data-intensive stacks like Spark or Databricks and the ability to write complex, optimized SQL for feature extraction and data validation
Benefits
Competitive compensationMeaningful ownership
Benefits
that go beyond the basics to support growth.
They are looking for a Machine Learning Engineer to build a world-class ML Ops foundation to accelerate the transition from model prototype to production.
The successful candidate will have 4-7 years of experience in software engineering, with at least 3 years focused on ML Ops or Data Engineering in a production environment.
Requirements
Proven experience in architecting and serving production-grade ML systems4–7 years of experience in software engineering, with at least 3 years focused specifically on ML Ops or Data Engineering in a production environmentExpert-level knowledge of AWS (or similar), Kubernetes, Airflow/Prefect, and Databricks/SparkTrack record of implementing request batching and model quantization to balance high-performance throughput with infrastructure costsExpert-level knowledge of core ML libraries (NumPy, Pandas, scikit-learn) and at least one deep learning framework (PyTorch or TensorFlow)Solid expertise in data-intensive stacks like Spark or Databricks and the ability to write complex, optimized SQL for feature extraction and data validation
Benefits
Competitive compensationMeaningful ownership
Benefits
that go beyond the basics to support growth.
The company
A
Addi Colombia
