Machine Learning Engineer II (100% Remote)

Key Skills

Apache Airflow, Continuous Integration & Continuous Delivery - CI/CD, Data science techniques, Google BigQuery, Google Cloud Platform (GCP), Kubeflow, Machine learning techniques, PyTorch, Scikit-learn, SPARK Programming, SQL, TensorFlow

Job Description

Supports cross-functional teams with designing and implementing ML-based solutions. Contributes to MLE internal tools and best practices.

ACCOUNTABILITIES

• Work with Engineers to integrate Data Science models into customer-facing solutions.
• Support model development through GCP service enablement and configuration.
• Contribute to roadmap for Data Science and MLE team tools and technology development
• Design and implement monitoring and alerting systems to maintain model performance and integrity.
• Work within the ML Engineering team to develop leverageable toolsets to standardize and streamline model implementations.
• Think in terms of iterative development, document, and communicate throughout products' data science lifecycle.
• Work closely with Data Scientists to efficiently scale models to meet production requirements.
• Optimize and fine-tune models to achieve peak performance and accuracy within resource constraints.
• Stay up-to-date on GCP services and best practices for DS/ML implementations.
• Work with Data Scientists to develop efficient, scalable ETL workflows to power ML solutions.

QUALIFICATIONS

• In-depth knowledge of Google Cloud Platform services, particularly Vertex AI, BigQuery, Dataproc.
• Extensive expertise with CI/CD and IaC best practices.
• Extensive expertise with distributed computing and big data technologies like Spark, Kubeflow, Airflow and SQL.
• Extensive expertise in Python and machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with Agile/XP software development.
• Experience with OGSM approach - strategy development and execution.

REQUIRED

• BS in Data Science, Computer Science, Machine Learning, Applied Mathematics, or equivalent quantitative field.
• 3+ years of progressively complex Data Science or analytics experience.
• 3+ years of experience as a Machine Learning Engineer with a proven track record of successful project delivery.

PREFERRED

• Master’s degree and/or Ph.D.
• Proficiency in Java/Scala or other languages.
• Retail experience
• Ecommerce experience