Machine Learning Engineer II

Job Description:

Summary:

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.

Responsibilities:

• 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.

Qualifications:

• Master'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.
• Familiarity with AWS cloud technologies (e.g., Glue, Sagemaker, Athena, Redshift).

• Solid understanding of machine learning algorithms and best practices.

• Experience with cloud computing platforms (e.g., AWS, Azure, GCP).

• Excellent communication and presentation skills.

Nice to Have:

• Familiarity with big data technologies (e.g., Spark, Iceberg, dbt).

• Experience with data visualization tools (e.g., Tableau, Streamlit, Plotly).

• Knowledge of retail and e-commerce.

The base salary range for this role is $119,500 - $190,000.00.

• The specific salary offered to a candidate may be influenced by a variety of factors including but not limited to the candidate’s relevant experience, education, and work location. In addition, this position is eligible for 401k and a new hire and annual equity grant. C08+ positions may also be eligible for annual bonus.

We offer different types of insurance and benefits, such as medical/Rx, vision, dental, life, disability, hospital indemnity, critical illness, and accident. We offer parental leave, family services benefits, backup dependent care, flexible spending accounts, telemedicine, pet adoption reimbursement, employee assistance program, and many discounts including 10% off pet insurance and 20% off at Chewy.com.

Exempt salary team members have unlimited PTO, subject to manager approval. Team members will receive six paid holidays per year. Team members may be eligible for paid sick and family leave in compliance with applicable state and local regulations.

Chewy is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, gender, citizenship, marital status, religion, age, disability, gender identity, results of genetic testing, veteran status, as well as any other legally-protected characteristic. If you have a disability under the Americans with Disabilities Act or similar law, and you need an accommodation during the application process or to perform these job requirements, or if you need a religious accommodation, please contact [email protected].

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