Machine Learning Engineer II

Our Opportunity:

We are seeking a talented and passionate Machine Learning Engineer II to join our growing team. In this role, you will play a crucial part in building and deploying machine learning solutions that empower our Chewy Customer Care teams. As a Machine Learning Engineer II, you will be a key contributor throughout the machine learning lifecycle, from data preparation and model development to deployment and monitoring. You will have the opportunity to work on diverse projects and contribute directly to the success of the company.

What You'll Do:

• Design and implement robust data pipelines for efficient data ingestion, processing, and feature engineering.
• Ensure data quality and consistency for model training and inference.
• Work with large datasets and apply data scaling techniques.
• Select and build appropriate machine learning models based on business requirements and data characteristics.
• Train and evaluate models using various techniques and metrics.
• Fine-tune models to achieve optimal performance and efficiency.
• Deploy machine learning models to production environments, ensuring scalability, reliability, and maintainability.
• Implement monitoring and alerting systems to track model performance and identify potential issues.
• Optimize models for inference speed and resource utilization.
• Work closely with data scientists, software engineers, and business stakeholders to understand requirements and deliver solutions.
• Effectively communicate technical concepts and findings to both technical and non-technical audiences.

What You'll Need:

• Bachelor's degree in Computer Science, Machine Learning, or a related field.
• 3+ years of experience as a Machine Learning Engineer or in a similar role.
• Strong programming skills in Python or another relevant language.
• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with SQL and relational databases.

Nice to Have:

• Familiarity with big data technologies (e.g., Spark, Iceberg, dbt).
• Familiarity with AWS cloud technologies (e.g., Glue, Sagemaker, Athena, Redshift).
• Experience with data visualization tools (e.g., Tableau, Streamlit, Plotly).
• Knowledge of retail and e-commerce.

• Solid understanding of machine learning algorithms and best practices.
• Experience with cloud computing platforms (e.g., AWS, Azure, GCP).
• Excellent communication and presentation skills.
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