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Machine Learning Engineer Jobs in Springfield, MO

Westrock

Supv, Mfg Ops

Springfield, MO · On-site

Monitor and track production daily goals for the Converting machines utilizing Key Performance ... Bachelor's degree (Business Management, Engineering or Operations Management) - Preferred * 3+ ...

Bespoke Labs

Data Engineer

Springfield, MO · On-site

$104K - $125K/yr

Must-Have Skills 3+ years of data engineering experience -- pipelines, ETL, data modeling in production or research settings Strong Python proficiency (numpy, pandas, Parquet, HDF5 are daily tools ...

Infra Pipe Solutions Ltd.

Packaging Operator

Springfield, MO · On-site

$15.50 - $18.75/hr

... and moving machinery. * Required to wear appropriate PPE including safety glasses, hearing ... Opportunities for learning and growth in manufacturing. * Competitive compensation and benefits ...

Infrapipes

Packaging Operator

Springfield, MO · On-site

$15.50 - $18.75/hr

... and moving machinery. * Required to wear appropriate PPE including safety glasses, hearing ... Opportunities for learning and growth in manufacturing. * Competitive compensation and benefits ...

Infrapipes

Packaging Operator

Springfield, MO

$15.50 - $18.75/hr

... and moving machinery. * Required to wear appropriate PPE including safety glasses, hearing ... Opportunities for learning and growth in manufacturing. * Competitive compensation and benefits ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Springfield, MO

Machine Learning Engineer information

See Springfield, MO salary details

$28.7K

$117.1K

$176K

How much do machine learning engineer jobs pay per year?

As of Jul 14, 2026, the average yearly pay for machine learning engineer in Springfield, MO is $117,132.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,300.00 and $141,000.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

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 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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

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 engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

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.

More about Machine Learning Engineer jobs
What job categories do people searching Machine Learning Engineer jobs in Springfield, MO look for? The top searched job categories for Machine Learning Engineer jobs in Springfield, MO are:
What cities near Springfield, MO are hiring for Machine Learning Engineer jobs? Cities near Springfield, MO with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Springfield, MO as of July 2026, with employment types broken down into 89% Full Time, 9% Part Time, and 2% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $117,132 per year, or $56.3 per hour.
System Administrator II-1

System Administrator II-1

O'Reilly Auto Parts

Springfield, MO • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 18 days ago

O'Reilly Auto Parts rating

5.3

Company rating: 5.3 out of 10

Based on 1,862 frontline employees who took The Breakroom Quiz

547th of 727 rated retailers

Job description

The System Admin II monitors system hardware, network, and infrastructure software performance, solves problems, and suggests improvements. This position manages authorized access to system resources with a heavy focus on Linux environments and evolving Cloud (GCP/Azure) infrastructures. A successful candidate demonstrates a high aptitude for learning and a proactive attitude toward maintaining system stability.
Responsibilities and Duties
  • System Maintenance: Complete operational tasks including data management, incident logging, systems monitoring, and disaster recovery. Perform critical system patching and environment changes.
  • Infrastructure Support: Support the day-to-day infrastructure and networks, with a primary focus on Linux administration and growing exposure to GCP or Azure cloud environments.
  • Issue Resolution: Provide initial fault isolation and support for technical issues; propose resolutions for approval by senior colleagues to ensure prompt system uptime.
  • Security & Compliance: Support the implementation of security measures (firewalls, encryption) and monitor performance to notify security experts of any vulnerabilities.
  • User Support: Provide advice and assistance to users to resolve basic queries and ensure application/website capabilities are understood by the business.
  • Continuous Learning: Actively develop own capabilities through formal training and coaching, specifically focusing on CI/CD pipelines and cloud technologies to stay abreast of industry trends.
  • On-Call & Scheduling: Participate in a 6 to 8-week on-call rotation (on for one week). Maintain flexibility for Monday-Friday daytime responsibilities alongside required evening maintenance windows.

Skills
Required:
  • Linux Foundations: Proficiency in monitoring, diagnosing, and fixing problems within Linux-based operating systems.
  • Cloud Navigation: Ability to navigate and manage cloud-based infrastructure (GCP preferred, Azure acceptable), including virtual machines and storage.
  • Modern DevOps Awareness: Basic understanding of CI/CD pipelines and the desire to integrate these into standard workflows.
  • Technical Troubleshooting: Identifies and resolves hardware, software, and network problems in line with prescribed solution options.
  • System Security: Maintains systems/services integrity, compliance, and continuity through proactive monitoring.
  • Adaptability & Aptitude: Ability to shift mindsets quickly to assess facts, learn new technologies (Aptitude), and maintain a positive, growth-oriented approach (Attitude).
  • Execution: Reviews requirements to develop appropriate action plans for software installation, configuration, and environment management.

Education & Experience
  • Education: Bachelor's Degree or Equivalent Level.
  • Experience: Experienced practitioner able to deal with the majority of situations (3 to 6 years preferred in a technical environment).
  • Managerial Experience: Basic experience of coordinating the work of others or managing help-desk workflows (4 to 6 months).

O'Reilly Auto Parts has a proven track record of growth and stability. O'Reilly is full of successful career stories and believes in a strong promote-from-within philosophy, encouraging you to grow your career along with the organization.
Total Compensation Package:
  • Competitive Wages & Paid Time Off
  • Stock Purchase Plan & 401k with Employer Contributions Starting Day One
  • Medical, Dental, & Vision Insurance with Optional Flexible Spending Account (FSA)
  • Team Member Health/Wellbeing Programs
  • Tuition Educational Assistance Programs
  • Opportunities for Career Growth

O'Reilly Auto Parts is an equal opportunity employer. The Company does not discriminate on the basis of race, religion, color, national origin or ancestry (including immigration status or citizenship), sex, sexual orientation, gender identity, pregnancy (including childbirth, lactation, and related medical conditions,) age (40 and over), veteran status, uniformed service member status, physical or mental disability, genetic information (including testing or characteristics) or another protected status as defined by local, state, or federal law, as applicable.
Qualified individuals with a disability may be entitled to reasonable accommodation under the Americans with Disabilities Act. If you require a reasonable accommodation during the application or employment process, please send an email to: rar@oreillyauto.com or call (800) 471-7431 option , and provide your requested accommodation, and position details.

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