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Machine Learning Engineer Jobs in Omaha, NE (NOW HIRING)

Isys Technologies

Journeyman Data Scientist

Omaha, NE

$90K - $125K/yr

Apply statistical analysis, machine learning, and data mining techniques. * Develop algorithms and predictive models using programming languages such as Python, R, or SQL. * Work with large datasets ...

GE HealthCare

AI Scientist

Bellevue, NE · On-site

Summary The AI Scientist will work in teams addressing statistical, machine learning and data ... D. in a "STEM" major (Science, Technology, Engineering, Mathematics) or equivalent field with 3 ...

GE HealthCare

AI Scientist

Bellevue, NE · On-site

Summary The AI Scientist will work in teams addressing statistical, machine learning and data ... D. in a "STEM" major (Science, Technology, Engineering, Mathematics) or equivalent field with 3 ...

Agile Defense

Data Scientist

Omaha, NE · On-site

This role is part of a multidisciplinary team integrating advanced analytics, machine learning, and engineering practices into mission-critical environments at Combatant Commands. You will help shape ...

Lorven Technologies

AI/ML Engineer

Omaha, NE · On-site

EXPERIENCE BUILDING AND DEPLOYING MACHINE LEARNING MODELS IN PRODUCTION ENVIRONMENTS * SOLID UNDERSTANDING OF DATA STRUCTURES, ALGORITHMS, AND SOFTWARE ENGINEERING BEST PRACTICES * EXPERIENCE WITH ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Omaha, NE

Machine Learning Engineer information

See Omaha, NE salary details

$30.1K

$123.2K

$185.1K

How much do machine learning engineer jobs pay per year?

As of Jul 20, 2026, the average yearly pay for machine learning engineer in Omaha, NE is $123,184.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,100.00 and $148,300.00 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 are the most commonly searched types of Machine Learning Engineer jobs in Omaha, NE? The most popular types of Machine Learning Engineer jobs in Omaha, NE are:
What are popular job titles related to Machine Learning Engineer jobs in Omaha, NE? For Machine Learning Engineer jobs in Omaha, NE, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Omaha, NE look for? The top searched job categories for Machine Learning Engineer jobs in Omaha, NE are:
What cities near Omaha, NE are hiring for Machine Learning Engineer jobs? Cities near Omaha, NE with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Journeyman Data Scientist

Journeyman Data Scientist

Isys Technologies

Omaha, NE

Full-time

Posted 25 days ago

Job description

Minimum Clearance RequiredSecretResponsibilities

Journeyman Data Scientist:

A Journeyman Data Scientist is typically a mid-level professional who works independently on data science projects, develops predictive models, analyzes complex datasets, and collaborates with stakeholders to support business decisions.

Job Duties
  • Collect, clean, and prepare structured and unstructured data from multiple sources.
  • Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
  • Develop, test, and deploy machine learning and statistical models.
  • Create predictive analytics solutions to support operational and strategic objectives.
  • Design and maintain data pipelines and analytical workflows.
  • Build dashboards, reports, and visualizations to communicate findings.
  • Validate model performance and recommend improvements.
  • Conduct data quality assessments and ensure data integrity.
  • Document methodologies, code, and analytical processes.
  • Support business units by translating complex data into actionable insights.
QualificationsTechnical Responsibilities
  • Apply statistical analysis, machine learning, and data mining techniques.
  • Develop algorithms and predictive models using programming languages such as Python, R, or SQL.
  • Work with large datasets using cloud and big data platforms.
  • Optimize model accuracy, scalability, and performance.
  • Implement model monitoring and maintenance procedures.
Business Responsibilities
  • Partner with business stakeholders to understand requirements and objectives.
  • Present findings and recommendations to technical and non-technical audiences.
  • Support data-driven decision-making across departments.
  • Identify opportunities for process improvement and automation.
Team Responsibilities
  • Collaborate with data engineers, software developers, analysts, and project managers.
  • Mentor junior data scientists and analysts.
  • Participate in code reviews and knowledge-sharing activities.
  • Follow organizational standards, governance, and security requirements.
Required Experience

Clearance Required: Secret or TS/SCI (not sure on this yet)

Education
  • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
  • Master's degree preferred for some organizations.
Professional Experience
  • Typically 3-7 years of experience in data science, analytics, machine learning, or a related field.
  • Experience working with large-scale datasets and production environments.
  • Proven track record of delivering analytical solutions that drive business outcomes.
Technical Skills
  • Programming: Python, R, SQL.
  • Machine Learning: Scikit-learn, TensorFlow, PyTorch, XGBoost.
  • Data Visualization: Tableau, Power BI, Matplotlib, Plotly.
Employment Type: FULL_TIME

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