Data Scientist, eComm - Machine Learning Engineer

$95,250 - $158,750/Yr

Walmart - Bentonville, AR

Full-time - Entry Level

Bentonville, AR

General Merchandise Retailers

About the position

The Machine Learning Engineer position within the Catalog Data Science team at Walmart focuses on enhancing data quality and compliance in the Walmart marketplace. This role involves developing and optimizing machine learning pipelines to detect policy violations and improve customer trust. The engineer will leverage advanced technologies such as GenAI, NLP, and deep learning to build scalable models that address complex challenges in product classification and compliance monitoring.

Responsibilities

• Evaluate and enhance Deep Learning practices within the Catalog Trust and Safety team.
• Use GenAI, NLP, Computer Vision, and other deep learning techniques to build models for classification, segmentation, and detection for Trust & Safety use cases.
• Collaborate cross-functionally with Compliance Business, Product, Operations, and other engineering teams to align on engagement strategies, business requirements, and model KPIs.
• Drive innovation in ML Architecture by implementing and optimizing highly scalable model architectures tailored to Trust & Safety.

Requirements

• Proficiency in Python, Spark, SQL, and associated Python packages commonly used for machine learning like Numpy, PyTorch, TensorFlow, scikit-learn.
• 2+ years of experience contributing high-quality code to production systems that operate at scale.
• Experience in designing, developing, and implementing complex machine learning pipelines that drive business results.
• Ability to solve intricate problems with multilayered data sets and multi-batch inferencing.
• Commitment to uphold ML engineering best practices - enforcing high standards for quality, reliability, and security in deployed machine learning solutions.
• Proactive approach in staying abreast with the latest AI/ML technologies and acting as a thought leader for ML Engineering within the organization and broader technical community.
• Solid understanding and practical experience with deploying ML pipelines using Docker, Kubernetes, Apache Airflow, Beam, Spark, Kafka.
• Practical experience with GCP, Azure, AWS or other cloud environments.
• Working knowledge of relational and NoSQL databases.
• Strong verbal and written communication skills.

Nice-to-haves

• Data science, machine learning, optimization models experience.
• Master's degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics.
• Successful completion of one or more assessments in Python, Spark, Scala, or R.
• Using open source frameworks (for example, scikit learn, tensorflow, torch).

Benefits

• 401(k) match
• Stock purchase plan
• Paid maternity and parental leave
• PTO
• Multiple health plans
• Short-term and long-term disability
• Company discounts
• Military Leave Pay
• Adoption and surrogacy expense reimbursement
• Live Better U education benefit program for associates.