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Machine Learning Engineer Jobs in Rogers, AR (NOW HIRING)

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Machine Learning Engineer information

See Rogers, AR salary details

$26.4K

$107.9K

$162.1K

How much do machine learning engineer jobs pay per year?

As of Sep 11, 2026, the average yearly pay for machine learning engineer in Rogers, AR is $107,904.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,100.00 and $129,900.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What cities near Rogers, AR are hiring for Machine Learning Engineer jobs?

Cities near Rogers, AR with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Rogers, AR as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 58% Full Time, 38% Part Time, and 2% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $107,904 per year, or $51.9 per hour.

Data Scientist III - Fraud Analytics & Machine Learning

Tontitown, AR • On-site

Sam's Club
Retail • 10K+ employees

Full-time

Re-posted 5 days ago


Key responsibilities

  • Transform billions of data points into solutions that identify fraud, reduce risk, and protect customers and the business.

  • Build analytical models to improve fraud detection, risk management, and business decision-making.

  • Partner with cross-functional teams to bring analytical solutions into production.


Sam's Club rating

6.5

Company rating: 6.5 out of 10

Based on 2,043 frontline employees who took The Breakroom Quiz


Job description

Position Summary... What you'll do...Fraud Analytics & Machine Learning | Walmart Global Tech Help Shape the Future of Retail Intelligence

Every day, millions of customers trust Walmart to deliver a seamless shopping experience. Behind that experience is one of the world's largest and most sophisticated commerce ecosystems—and protecting it from fraud requires exceptional data scientists.

As a Data Scientist III on the Inkiru Data Science team, you'll transform billions of data points into intelligent solutions that identify fraud, reduce risk, and protect both customers and the business. You'll partner with engineers, product managers, and business leaders to build analytics and machine learning solutions that directly influence decisions at global scale.

If you're energized by solving complex problems, uncovering meaningful insights, and seeing your work deployed into production, we'd love to meet you.

Why This Role Matters

Fraud evolves every day—and so do we.

Our team combines advanced analytics, statistical modeling, machine learning, and AI to stay ahead of emerging threats while delivering a seamless experience for customers and associates.

Your work won't sit in a report.

It will power real products, influence strategic decisions, and help protect one of the largest retailers in the world.

What You'll Do

You'll make an impact by:

  • Detecting emerging fraud trends using large-scale behavioral, transactional, and operational data.

  • Building analytical models that improve fraud detection, risk management, and business decision-making.

  • Creating intuitive dashboards and visualizations that help leaders quickly understand key business metrics.

  • Partnering closely with Product, Engineering, Data Science, and Business teams to bring analytical solutions into production.

  • Exploring new analytical techniques—including machine learning and AI—to solve evolving business challenges.

  • Improving data quality through validation, governance, and scalable analytical processes.

  • Communicating complex findings through compelling storytelling that drives action.

What You'll Work With

You'll leverage modern technologies including:

  • Python

  • SQL

  • Spark

  • Hive

  • BigQuery

  • Distributed computing platforms

  • Tableau

  • Power BI

  • Machine Learning frameworks

  • Cloud-scale analytics platforms

  • AI-assisted analytics and modern data science workflows

Why You'll Love This Team

You'll join a collaborative team that values curiosity, experimentation, and continuous learning.

Here you'll have opportunities to:

  • Solve problems at one of the largest scales in retail.

  • Work with experienced data scientists and machine learning engineers.

  • Influence product strategy with data-driven insights.

  • Build solutions that move from concept into production.

  • Learn new technologies while working on meaningful business challenges.

  • Grow your career through mentorship, leadership opportunities, and cross-functional collaboration.

What Success Looks Like

Within your first year, you'll:

  • Deliver analytical solutions that influence fraud strategy.

  • Build trusted relationships across Product, Engineering, and Business teams.

  • Create scalable dashboards and reporting used by leadership.

  • Improve fraud detection through innovative analytical approaches.

  • Contribute to production-ready data science solutions that create measurable business value.

What You'll Bring

We're looking for someone who combines technical excellence with curiosity and business acumen.

Preferred qualifications include:

  • Strong analytical and statistical problem-solving skills.

  • Experience working with large, complex datasets.

  • Proficiency in SQL and Python (R is also welcome).

  • Experience with distributed computing technologies such as Spark, Hive, or BigQuery.

  • Familiarity with data visualization tools including Tableau, Power BI, or Looker.

  • Ability to communicate technical concepts clearly to both technical and non-technical audiences.

  • Passion for solving ambiguous problems using data.

  • Bachelor's degree in a STEM field with 3+ years of relevant experience, or a Master's degree with 1+ years of experience.

Bonus Points If You Have
  • Experience in fraud analytics, financial risk, cybersecurity, or trust and safety.

  • Experience building or deploying machine learning models.

  • Knowledge of experimentation, causal inference, or advanced statistical techniques.

  • Experience with Generative AI, LLMs, or AI-assisted analytics.

  • Experience working in cloud-native data environments.

Why Walmart Global Tech

Technology is reshaping how the world shops.

At Walmart Global Tech, you'll help solve problems that few companies can match in complexity or scale. Our teams build products and platforms that serve millions of customers, associates, and suppliers every day.

Here, your work has immediate impact.

You'll have access to world-class data, modern technologies, and talented teammates—all while helping build the future of retail.

Whether your passion is analytics, machine learning, artificial intelligence, or data engineering, you'll find opportunities to learn, innovate, and grow your career.

‎ 

Minimum Qualifications...

Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.

Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics or related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field. Option 3: 4 years' experience in an analytics or related field. Preferred Qualifications...

Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.

Data science, machine learning, optimization models, 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), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart’s accessibility standards and guidelines for supporting an inclusive culture. Primary Location... 2101 Se Simple Savings Dr, Bentonville, AR 72712-4304, United States of America Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.

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