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Machine Learning Engineer (MLOps Engineer) - AA

1 days ago

  • usaRemote, Colombia / Remote, Costa Rica
  • usaFull-Time/Salary
  • usaData & AI
  • usaRemote
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Overview: - Machine Learning Engineer role at Gorilla Logic - Part of a team building a ML Platform on Databricks - Utilizes open source technologies (Python, Spark, Kafka, Delta, Bazel, MLFlow) Key Responsibilities: - Design and build ML systems, frameworks, pipelines, libraries, utilities, and tools - Translate data science prototypes into scalable production implementations - Partner with data scientists to optimize data pipelines - Build ML Platform for new model implementation - Develop reusable pipelines from data acquisition to model output - Identify and propose new ML applications to improve business results - Develop, deploy, maintain, and manage scalable data transformation, ML, and deep learning code - Perform code reviews for architecture, code, and data standards Requirements/Skills/Qualifications: - 3+ years of Machine Learning Engineering experience, with MLOps focus - Experience with Python libraries (MLFlow, MLRun, scikit-learn, PyTorch, MLLib) - Proficient in Python (PySpark), SQL; knowledge of Scala, Java, C#, JavaScript - Understanding of programming fundamentals (OOP, data structures, algorithm design) - Experience with distributed compute engines (Apache Spark), cloud-based databases (Snowflake, Bigquery, Redshift), Data Lakes (Azure Data Lake, S3) - Expertise in building scalable ML systems - Experience integrating ML models in production (batch, streaming, online) - Fluency in Machine Learning algorithms - Experience in writing data pipeline and ML libraries and utilities - Industry experience in productionizing ML systems Compensation & Benefits: - Not specified in the provided job description.
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Gorilla Logic

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