Senior Machine Learning Engineer - Production ML & Big Data

Compunnel, Inc.; Philadelphia (Philadelphia County); Presencial; USD 140.000 - 200.000; Jornada completa

Descripción de la vacante

Compunnel, Inc. is seeking a highly experienced Senior Machine Learning Engineer to join a team building production-grade predictive systems for large-scale enterprise applications.

This role focuses on end-to-end ML engineering with Python, PySpark, and big data platforms such as Databricks or Snowflake. The ideal candidate will design, develop, deploy, and maintain production ML models, monitor performance, and collaborate with data engineering and software teams to ensure reliability and

Formación

• Built machine learning models from scratch.
• Experience with Python and PySpark.
• Experience deploying models to production.
• Strong data preprocessing and feature engineering.
• Experience with large-scale data platforms (Databricks/Snowflake).
• Mentoring junior engineers and collaborating with teams.
• Knowledge of model evaluation metrics.

Responsabilidades

• Design, build, train, validate, and deploy production ML models.
• Develop predictive models using various algorithms.
• Build scalable PySpark pipelines for large datasets.
• Write clean, production-grade Python code and APIs.
• Monitor models and manage retraining and drift.
• Lead technical reviews and mentor junior engineers.

Conocimientos

Python development

Machine Learning engineering

Production monitoring

Mentoring

Big data analytics

Educación

Herramientas

Databricks

Snowflake

Delta Lake

REST APIs

Descripción del empleo

Compunnel, Inc. is seeking a highly experienced Senior Machine Learning Engineer to join a team building production-grade predictive systems for large-scale enterprise applications.

This role focuses on end-to-end ML engineering with Python, PySpark, and big data platforms such as Databricks or Snowflake. The ideal candidate will design, develop, deploy, and maintain production ML models, monitor performance, and collaborate with data engineering and software teams to ensure reliability and