Senior, Machine Learning Engineer (TEST REQ - DO NOT APPLY)

Walmart•Bentonville, AR

1d•$110,000 - $220,000

About The Position

The Senior Machine Learning Engineer delivers and supports machine-learning features, models, services, APIs, and data pipelines in collaboration with engineering, data science, and product teams. The role contributes to scalable ML solution design, selects appropriate algorithms and technologies, and builds production-ready systems that meet business and customer needs. The position covers the end-to-end ML lifecycle, including data sourcing, feature engineering, training, testing, deployment, evaluation, and monitoring. It applies MLOps practices such as CI/CD, automated retraining, model versioning, and telemetry, and monitors deployed models for drift, latency, and performance. The engineer also applies responsible and secure AI practices, including enterprise governance, data privacy and security, and prompt engineering, LLM evaluation, and fine-tuning for domain-specific generative AI applications. The role includes technical ownership, sound technical judgment, collaboration across teams, knowledge sharing, and mentoring junior engineers. It also encompasses supervisory responsibilities such as hiring, training, mentoring, assigning duties, recognizing associates, and supporting their development. The position promotes continuous improvement, inclusion, integrity, compliance, and customer- and member-focused results.

Requirements

Bachelor’s degree in computer science, computer engineering, computer information systems, software engineering, or a related area, plus 3 years of experience in software engineering, machine-learning engineering, AI systems, or a related area; alternatively, 5 years of experience in one of those areas.
Experience delivering software, machine-learning, or AI systems.
Ability to work with ML frameworks such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or Spark ML, and programming languages such as Python, SQL, Java, C++, or R.
Ability to apply model evaluation, validation, and monitoring practices.
Ability to work collaboratively across teams and communicate complex ideas to technical and non-technical stakeholders.

Nice To Haves

Master’s degree in computer science, computer engineering, computer information systems, software engineering, or a related area, and 1 year of experience in software engineering, machine-learning engineering, AI systems, or a related area.
Prior work experience in accessibility best practices.
Prior work experience creating inclusive digital experiences, including knowledge of WCAG 2.2 AA standards, assistive technologies, and integrating digital accessibility.

Responsibilities

Deliver scoped ML features and models in collaboration with engineers, data scientists, and product teams.
Own implementation, iteration, testing, and support for assigned services, APIs, data pipelines, or ML model components.
Translate requirements into sustainable technical solutions and ensure alignment with platform and system objectives.
Contribute to the design of robust, scalable ML systems for business and customer challenges.
Select and apply suitable machine-learning algorithms, frameworks, and programming languages based on performance, maintainability, and explainability needs.
Support experimentation frameworks, model evaluation strategies, and feature-engineering pipelines.
Write clean, efficient, production-ready code for ML applications and integrate external or custom models and APIs into enterprise systems.
Implement and maintain reliable data ingestion, preprocessing, and transformation pipelines.
Apply MLOps practices, including CI/CD for ML, automated retraining, model versioning, and telemetry.
Execute the ML lifecycle from data sourcing and feature engineering through training, testing, deployment, and monitoring.
Evaluate and validate models using appropriate metrics for accuracy, fairness, and compliance.
Monitor deployed models for drift, latency, and performance degradation, and initiate retraining or updates when needed.
Mentor junior engineers on coding standards, pipeline best practices, and model evaluation techniques.
Participate in architectural and technical discussions and contribute to scalable, maintainable, and compliant solutions.
Promote knowledge sharing through code reviews, documentation, and collaborative workshops.
Engineer ML pipelines with attention to data security, privacy, and compliance with enterprise AI governance standards.
Apply prompt engineering, LLM evaluation, and fine-tuning practices for domain-specific generative AI applications.
Document and track experiments with tools such as MLflow or Weights & Biases.
Take responsibility for deliverables, resolve issues, and drive projects to completion while meeting quality standards and business objectives.
Coordinate and oversee job-related activities and assignments, maintain stakeholder relationships, support plans and initiatives, communicate goals, measure progress, and address improvement opportunities.
Ensure compliance with company policies and procedures and support company mission, values, ethics, and integrity standards.
Supervise and develop associates through hiring, training, mentoring, assigning duties, recognition, and opportunities for development.
Foster respect, belonging, collaboration, and strong working relationships with team members and business partners.
Promote integrity, ethical conduct, compliance, accountability, and a culture where concerns can be raised without retaliation.
Deliver business results with a customer- and member-first, data-informed perspective.
Seek feedback, encourage learning and intelligent risk-taking, and implement continuous improvements using new digital tools and ways of working.

Benefits

Competitive pay and performance-based bonus awards.
Medical, vision, and dental coverage.
401(k), stock purchase, and company-paid life insurance.
Paid time off, including sick leave, parental leave, family care leave, bereavement leave, jury duty, and voting leave.
Short-term and long-term disability.
Company discounts and Military Leave Pay.
Adoption and surrogacy expense reimbursement.
PTO and/or PPTO for vacation, sick leave, holidays, or other purposes, subject to job classification and length of employment.
Live Better U education benefit program, with tuition, books, and fees paid for eligible programs from high school completion to bachelor’s degrees, English Language Learning, and short-form certificates.
Stock compensation may be included for certain positions.