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Weekend Walmart Data Engineer Jobs in Alabama (NOW HIRING)

International Paper

Capital Projects Engineer

Selma, AL · On-site

$100K - $137K/yr

Review of design and engineering data (drawings and other documents) to verify completeness and ... Willing to work weekends and extra hours on shutdowns to meet project goals * Fulfill weekend duty ...

YEDLA LLC

Engineer

Montgomery, AL

Must have the ability to assimilate complex information, data, etc. from disparate sources and ... weekends, holidays, and on-call shifts Benefits Competitive pay Health, dental, and vision ...

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Weekend Walmart Data Engineer information

What is the difference between Weekend Walmart Data Engineer vs Weekend Walmart Data Analyst?

AspectWeekend Walmart Data EngineerWeekend Walmart Data Analyst
Required CredentialsBachelor's in Computer Science, Data Engineering certificationsBachelor's in Statistics, Data Analysis certifications
Work EnvironmentData warehouses, cloud platforms, technical teamsBusiness units, reporting tools, cross-functional teams
Employer & Industry UsageRetail industry, Walmart-specific data systemsRetail industry, Walmart sales and customer data analysis

Weekend Walmart Data Engineers focus on building and maintaining data pipelines and infrastructure, requiring technical skills and engineering certifications. In contrast, Weekend Walmart Data Analysts interpret data to generate insights, often using statistical tools and reporting software. Both roles are essential in Walmart's data ecosystem but differ in technical depth and daily responsibilities.

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Weekend Walmart Data Engineer jobs near you

Mid-level Machine Learning Engineer

Astrion

Huntsville, AL

$135K - $150K/yr

Full-time

Re-posted 8 days ago

Job description

Overview

Machine Learning Engineer

JOB LOCATION: Huntsville, Al

JOB STATUS: Full-time

CLEARANCE: TS/SCI w CI/Poly

TRAVEL: As needed

Astrion seeking a Machine Learning Engineer to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government customer in Huntsville, Alabama.

This role will be responsible for delivering automation to key national security missions interacting with petabyte-scale data on supercomputing resources.

The ideal candidate will have a background in AI/ML model development and deployment and have experience in Python programming, handling SQL databases, and working in command line interfaces.

The team will work with technologies including:

  • Open source, commercial, and government software packages such as Docker, Python, Jupiter Notebooks, PostgreSQL, and other tools.
  • Leverage GitOps patterns and CI/CD with tools like GitLab and GitHub.

Work Environment

  • Working conditions are normal for an office environment.
  • Fast paced, deadline-oriented environment.
  • May require periods of non-traditional working hours including consecutive nights or weekends (if applicable).

REQUIRED QUALIFICATIONS / SKILLS

  • TS/SCI with CI Polygraph
  • Degree in Computer Science, Statistics, Mathematics, Physics or another quantitative field.
  • 1-3 years of experience working with ML frameworks
  • Programming proficiency in Python and extensive knowledge of ML frameworks, libraries data structures, and data modeling.
  • Solid understanding of the full ML development lifecycle.
  • Experience working with SQL and NoSQL databases.
  • Experience with both Linux and Windows operating systems.
  • Knowledge of CI/CD and Agile methodologies.
  • Understanding of software design and system integration.

PREFERRED QUALIFICATIONS / SKILLS

  • Experience with petabyte scale data sets
  • Experience with multi-INT analytics
  • Experience deploying, monitoring, and scaling models in production environments

RESPONSIBILITIES

  • Integrate ML systems with other software components, ensuring that machine learning pipelines work within the overall product architecture.
  • Manage the transition from prototype to production, including setting up model deployment pipelines and monitoring solutions.
  • Construct optimized data pipelines to feed ML models; run tests and experiments and document findings.
  • Monitor model performance post-deployment including managing model drift, rollback, and failure scenarios.
  • Write clean, testable, maintainable code in Python and other languages.

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