Machine Learning Engineer
hace 2 semanas
Machine Learning Engineer:
The ML Engineer is responsible for architecting the productionalized solution around rules-based and AI/ML models to integrate predictions seamlessly into the business processes, ensuring governance, resiliency, explainability, reproducibility, and scalability of the models.
ML Platform Engineer Responsibilities:
- Lead and consult with business stakeholders and data science teams to define data engineering and MLOps requirements.
- Solving complex problems with multilayered data sets, as well as optimizing existing machine learning libraries and frameworks.
- Developing reusable data and feature stores for rulesbased and AI/ML models.
- Developing alerting tool frameworks for monitoring productionized model performance and effectiveness.
- Automate deployments incorporating MLOps best practices into productionalized solutions.
- Document frameworks and machinelearning processes.
- Build simple frontend reporting solution for shipboard engineers to consume the insights. (web app development)
Required Skills:
- Experience building scalable machine learning systems and datadriven products working with crossfunctional teams.
- Welldeveloped software engineering fundamentals, including use of proper development, QA, and production environments, and the ability to write productionlevel code when needed.
- Experience creating a python package
- Proficiency in Python and experience with common data analytics packages (e.g. Numpy, Pandas, Sklearn, PySpark).
- Proficiency in Databricks & MLFlow
- Proficiency in SQL.
- Good communication skills and the ability to understand and synthesize requirements across multiple project domains.
- Works effectively with crossfunctional teams
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