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Machine Learning Engineer Jobs in Topeka, KS (NOW HIRING)

Bespoke Labs

Machine Learning Engineer

Topeka, KS · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Wood Plc

Software Development Engineer

Topeka, KS · On-site +1

Experience with Machine Learning, Deep Learning, and/or AI * Experience with data processing ... leader in engineering and consultancy across energy and the built environment, helping to unlock ...

Miamioh

Director, Business Intelligence Team

Hoyt, KS

$155K/yr

Build, lead, and develop a high-performing, multi-disciplinary team of analytics, data engineering ... Experience applying predictive analytics, machine learning, or AI capabilities to business or ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Topeka, KS

Machine Learning Engineer information

See Topeka, KS salary details

$29.8K

$122K

$183.4K

How much do machine learning engineer jobs pay per year?

As of Jul 17, 2026, the average yearly pay for machine learning engineer in Topeka, KS is $122,016.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,200.00 and $146,900.00 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 Topeka, KS? The most popular types of Machine Learning Engineer jobs in Topeka, KS are:
What are popular job titles related to Machine Learning Engineer jobs in Topeka, KS? For Machine Learning Engineer jobs in Topeka, KS, the most frequently searched job titles are:
What cities near Topeka, KS are hiring for Machine Learning Engineer jobs? Cities near Topeka, KS with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Topeka, KS as of July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $122,016 per year, or $58.7 per hour.
Machine Learning Engineer

Machine Learning Engineer

Keysight Technologies, Inc.

Topeka, KS

$145K - $266K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 8 days ago

Keysight Technologies rating

8.1

Company rating: 8.1 out of 10

Based on 20 frontline employees who took The Breakroom Quiz

42nd of 143 rated electronics manufacturers

Job description

Overview

Keysight is on the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.

Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.

We are seeking a Machine Learning Engineer to lead the design, development, and deployment of scalable machine learning models that power business decisions across the enterprise. This role combines technical depth in ML/AI with a strong understanding of business domains such as Sales, Service, Finance, Order Fulfillment, and Supply Chain. You will collaborate closely with Data Scientists, Data Engineers, and business partners to build production-ready solutions that drive measurable impact.


Responsibilities

1. Machine Learning Development & Deployment

  • Design and implement supervised and unsupervised models for predictive analytics, including churn prediction, demand forecasting, renewal risk scoring, and cross-sell/upsell opportunity identification.
  • Translate business problems into ML frameworks and production solutions that improve efficiency, revenue, or customer experience.
  • Build, optimize, and maintain ML pipelines using tools such as MLflow, Airflow, or Kubeflow.

2. Cross-Functional ML Use Cases

  • Partner with teams across Sales (e.g., lead scoring, next-best action), Customer Service (e.g., case deflection, sentiment analysis), Finance (e.g., revenue forecasting, fraud detection), Supply Chain (e.g., inventory optimization, ETA prediction), and Order Fulfillment (e.g., delivery risk modeling) to define impactful ML use cases.
  • Develop domain-specific models and continuously improve them using feedback loops and real-world performance data.

3. Model Governance and MLOps

  • Ensure robust model monitoring, versioning, and retraining strategies to keep models reliable in dynamic environments.
  • Work closely with DevOps and Data Engineering teams to automate deployment, CI/CD workflows, and cloud-native ML infrastructure (AWS/GCP/Azure).

4. Data Engineering and Feature Architecture

  • Collaborate with data engineers to define feature stores, data quality checks, and model-ready datasets on platforms like Snowflake or Databricks.
  • Perform feature selection, transformation, and engineering aligned with each domain’s business logic.

5. Communication & Stakeholder Collaboration

  • Present technical insights and model results to business and executive stakeholders in a clear, actionable format.
  • Work with Product Owners and Program Managers to scope, prioritize, and plan delivery of ML projects.

Qualifications

Required:

  • 4-6 years of experience in machine learning, data science, or AI engineering, with a strong software engineering foundation.
  • Proficiency in Python, and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar.
  • Experience deploying models into production using ML pipelines and orchestration frameworks.
  • Strong understanding of data structures, SQL, and cloud platforms (e.g., AWS SageMaker, Azure ML, or GCP Vertex AI).

Preferred:

  • Experience supporting business functions such as Finance, Sales, or Operations with ML use cases.
  • Familiarity with MLOps tools (MLflow, SageMaker Pipelines, Feature Store).
  • Exposure to enterprise data platforms (e.g., Snowflake, Oracle Fusion, Salesforce).
  • Background in statistics, forecasting, optimization, or recommendation systems.

The level of role will be based on applicable experience, education and skills; Most offers will be between the minimum and the midpoint of the Salary Range listed below.

California Pay range: MIN $145,000.00 - MAX $266,000.00

Colorado pay range: MIN $135,000.00 - MAX $225,000.00

District of Columbia pay range: MIN $135,000.00 - MAX $225,000.00

Hawaii pay range: MIN $135,000.00 - MAX $225,000.00

Illinois pay range: MIN $135,000.00 - MAX $225,000.00

Maryland pay range:  MIN $145,000.00 - MAX $243,000.00

Massachusetts pay range: MIN $145,000.00 - MAX $243,000.00

Minnesota pay range: MIN $135,000.00 - MAX $225,000.00

New Jersey City pay range: MIN $126,000.00 - MAX $211,000.00

New York pay range: MIN $160,000.00 - MAX $266,000.00

Vermont pay range: MIN MIN $135,000.00 - MAX $225,000.00

Washington state pay range:  MIN $145,000.00 - MAX $243,000.00

Note: For other locations, pay ranges will vary by region.

This role is eligible for Keysight's Variable Pay Bonus Program

US Employees may be eligible for the following benefits:

  • Medical, dental and vision
  • Health Savings Account
  • Health Care and Dependent Care Flexible Spending Accounts
  • Life, Accident, Disability insurance
  • Business Travel Accident and Business Travel Health
  • 401(k) Plan
  • Flexible Time Off, Paid Holidays
  • Paid Family Leave
  • Discounts, Perks
  • Tuition Reimbursement
  • Adoption Assistance
  • ESPP (Employee Stock Purchase Plan)
  • Restricted Stock Units

Careers Privacy Statement ***Keysight is an Equal Opportunity Employer.***

Keysight Technologies Inc. is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other protected categories under all applicable laws. 

Qualifications:

Required:

  • 4-6 years of experience in machine learning, data science, or AI engineering, with a strong software engineering foundation.
  • Proficiency in Python, and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar.
  • Experience deploying models into production using ML pipelines and orchestration frameworks.
  • Strong understanding of data structures, SQL, and cloud platforms (e.g., AWS SageMaker, Azure ML, or GCP Vertex AI).

Preferred:

  • Experience supporting business functions such as Finance, Sales, or Operations with ML use cases.
  • Familiarity with MLOps tools (MLflow, SageMaker Pipelines, Feature Store).
  • Exposure to enterprise data platforms (e.g., Snowflake, Oracle Fusion, Salesforce).
  • Background in statistics, forecasting, optimization, or recommendation systems.

The level of role will be based on applicable experience, education and skills; Most offers will be between the minimum and the midpoint of the Salary Range listed below.

California Pay range: MIN $145,000.00 - MAX $266,000.00

Colorado pay range: MIN $135,000.00 - MAX $225,000.00

District of Columbia pay range: MIN $135,000.00 - MAX $225,000.00

Hawaii pay range: MIN $135,000.00 - MAX $225,000.00

Illinois pay range: MIN $135,000.00 - MAX $225,000.00

Maryland pay range:  MIN $145,000.00 - MAX $243,000.00

Massachusetts pay range: MIN $145,000.00 - MAX $243,000.00

Minnesota pay range: MIN $135,000.00 - MAX $225,000.00

New Jersey City pay range: MIN $126,000.00 - MAX $211,000.00

New York pay range: MIN $160,000.00 - MAX $266,000.00

Vermont pay range: MIN MIN $135,000.00 - MAX $225,000.00

Washington state pay range:  MIN $145,000.00 - MAX $243,000.00

Note: For other locations, pay ranges will vary by region.

This role is eligible for Keysight's Variable Pay Bonus Program

US Employees may be eligible for the following benefits:

  • Medical, dental and vision
  • Health Savings Account
  • Health Care and Dependent Care Flexible Spending Accounts
  • Life, Accident, Disability insurance
  • Business Travel Accident and Business Travel Health
  • 401(k) Plan
  • Flexible Time Off, Paid Holidays
  • Paid Family Leave
  • Discounts, Perks
  • Tuition Reimbursement
  • Adoption Assistance
  • ESPP (Employee Stock Purchase Plan)
  • Restricted Stock Units

Careers Privacy Statement ***Keysight is an Equal Opportunity Employer.***

Keysight Technologies Inc. is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other protected categories under all applicable laws. 

Education:UNAVAILABLEEmployment Type: UNAVAILABLE

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