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Machining Engineer Jobs in Arkansas (NOW HIRING)

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

Quora

$139K - $168K/yr

  • Medical

  • Dental

  • Vision

  • PTO

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning systems, building performant and reliable LLM applications and collaborating with our product team to ...

Quora

$139K - $168K/yr

  • Medical

  • Dental

  • Vision

  • PTO

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning systems, building performant and reliable LLM applications and collaborating with our product team to ...

Saint Jean Industries

Programmer

Heber Springs, AR · On-site

$22.50 - $30.75/hr

The CNC Programmer will be responsible for writing, modifying, and optimizing CNC programs for milling, turning, and multi-axis machines to produce precision parts and components. The ideal candidate ...

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All JobsMachining Engineer JobsMachining Engineer Jobs in Arkansas

Machining Engineer information

See Arkansas salary details

$54.6K

$75.1K

$106.3K

How much do machining engineer jobs pay per year?

As of Aug 13, 2026, the average yearly pay for machining engineer in Arkansas is $75,093.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,700.00 and $80,200.00 per year, depending on experience, location, and employer.

What are some common challenges machining engineers face when optimizing manufacturing processes?

Machining Engineers frequently encounter challenges such as minimizing cycle times while maintaining product quality, troubleshooting equipment issues, and ensuring efficient use of materials. They must balance tight production deadlines with the need for precision and adherence to safety standards. Collaboration with operators, design engineers, and quality control teams is essential to identify process improvements and implement new technologies. Adapting to rapidly advancing manufacturing technologies and integrating automation can also present ongoing learning opportunities and challenges.

What is a machining engineer?

Machining Engineers are professionals who design, develop, and optimize processes for manufacturing parts using machining methods such as milling, turning, drilling, and grinding. They work with a variety of materials and oversee the programming, setup, and operation of machine tools, often using computer-aided manufacturing (CAM) software. Their main goal is to ensure products are manufactured efficiently, accurately, and cost-effectively, while maintaining quality and safety standards. Machining Engineers often collaborate with design, production, and quality teams to improve processes and troubleshoot issues in the manufacturing environment.

What is the difference between Machining Engineer vs Manufacturing Engineer?

AspectMachining EngineerManufacturing Engineer
CredentialsTypically requires a degree in mechanical or manufacturing engineering, with certifications in CAD/CAM softwareSimilar credentials, often with additional focus on production processes and quality management
Work EnvironmentWorks primarily in machine shops, CNC facilities, or manufacturing plants focusing on machining processesWorks across entire production lines, including process planning, quality control, and equipment optimization
Industry UsageCommonly employed in industries with heavy machining needs like aerospace, automotive, and toolingUsed broadly in manufacturing sectors including electronics, consumer goods, and industrial equipment

While both roles require engineering knowledge and involve manufacturing processes, Machining Engineers focus specifically on machining operations and CNC programming, whereas Manufacturing Engineers oversee entire production systems. The choice depends on whether you prefer specialized machining work or broader manufacturing process management.

What are the key skills and qualifications needed to thrive as a machining engineer?

To thrive as a Machining Engineer, you need a solid background in mechanical engineering, manufacturing processes, and materials science, often supported by a bachelor's degree in engineering. Proficiency with CAD/CAM software, CNC programming, and knowledge of quality control systems are typically required. Strong problem-solving abilities, attention to detail, and effective communication set outstanding professionals apart in this role. These skills are crucial for optimizing machining operations, ensuring product quality, and driving continuous process improvement in manufacturing environments.

What are popular job titles related to Machining Engineer jobs in Arkansas?

For Machining Engineer jobs in Arkansas, the most frequently searched job titles are:

What job categories do people searching Machining Engineer jobs in Arkansas look for?

The top searched job categories for Machining Engineer jobs in Arkansas are:

What are popular job titles related to Machining Engineer jobs in AR?

For Machining Engineer jobs in AR, the most frequently searched job titles are:

Machining Engineer jobs near you
Infographic showing various Machining Engineer job openings in Arkansas as of August 2026, with employment types broken down into 87% Full Time, 7% Part Time, and 6% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $75,093 per year, or $36.1 per hour.

Machine Learning Engineer, Specialist

慨正橡扯

Malvern, AR • On-site

$90 - $120/hr

Other

Posted 8 days ago

Job description

We are seeking an experienced Machine Learning Engineer to join our AI/ML Engineering team. You will be responsible for developing and optimizing complex data pipelines, integrating model pipelines, and building scalable AI/ML solutions, including large language models (LLMs). The ideal candidate will possess a robust background in traditional machine learning, applied GenAI, and significant experience with large datasets and AWS cloud-based AI/ML services.

Supports and performs the development and programming of machine learning integrated software algorithms to structure, analyze, and leverage data in a production environment.

Core Responsibilities
  • Leverages data pipeline designs and supports the development of data pipelines to support model development. Proficient with software tools that develop data pipelines in a distributed computing environment (PySpark, GlueETL).
  • Supports integration of model pipelines in a production environment. Develops understanding of SDLC for model production.
  • Reviews pipeline designs, makes data model design changes as needed. Documents and reviews design changes with data science teams.
  • Supports data discovery & automated ingestion for model development. Performs detailed analysis of raw data sources for data quality, applies business context, and model development needs.
  • Engages with internal stakeholders to understand and probe business processes in order to develop hypotheses. Brings structure to requests and translates requirements into an analytic approach. Participates in and influences ongoing business planning and departmental prioritization activities.
  • Runs model monitoring scripts, follows process for alerts to management as needed. Addresses issues found in data pipelines from model monitoring alerts.
  • Participates in special projects and performs other duties as assigned.
Qualifications
  • Undergraduate degree or equivalent experience; a graduate degree is preferred.
  • Minimum of 5 years of relevant work experience.
  • At least 3 years of hands‑on experience designing ETL pipelines using AWS services (e.g., Glue, SageMaker).
  • Proficiency in programming languages, particularly Python (including PySpark, PySQL) and familiarity with machine learning libraries and frameworks.
  • Strong understanding of cloud technologies, including AWS and Azure, and experience with NoSQL databases.
  • Familiarity with Feature Store usage, LLMs, GenAI, RAG, Prompt Engineering, and Model Evaluation.
  • Experience with API design and development is a plus.
  • Solid understanding of software engineering principles, including design patterns, testing, security, and version control.
  • Knowledge of Machine Learning Development Lifecycle (MDLC) best practices and protocols.
  • Understanding of solution architecture for building end-to-end machine learning data pipelines.
Special Factors

Sponsorship

Vanguard is not offering visa sponsorship for this position.

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