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Machine Learning Engineer Jobs in Kansas City, MO

Data Scientist 2

Olathe, KS · On-site

$110 - $160/hr

In addition, under guidance or with minimal supervision, this role will apply machine learning, statistical analysis, and data engineering techniques to address challenging business problems.

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

... machine learning, and 3D printing to produce some of the industry's most complex precision ... Partner with Programming to optimize cutting parameters and improve machining performance

... machine learning algorithms and predictive modeling techniques - Collaborating with clients to validate outcomes and incorporate feedback into data solutions - Directing teams through complex ...

... Machine Learning. * "Full-Stack" Capability: Demonstrated ability to act as a bridge between Data Science, Engineering, and Product--taking raw telemetry, applying statistical/ML models, and ...

Showing results 41-60

Machine Learning Engineer information

See Kansas City, MO salary details

$30.7K

$125.5K

$188.6K

How much do machine learning engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for machine learning engineer in Kansas City, MO is $125,503.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,900.00 and $151,100.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

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 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 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.

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.

What are the most commonly searched types of Machine Learning Engineer jobs in Kansas City, MO?

The most popular types of Machine Learning Engineer jobs in Kansas City, MO are:

What are popular job titles related to Machine Learning Engineer jobs in Kansas City, MO?

For Machine Learning Engineer jobs in Kansas City, MO, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer jobs in Kansas City, MO look for?

The top searched job categories for Machine Learning Engineer jobs in Kansas City, MO are:

What cities near Kansas City, MO are hiring for Machine Learning Engineer jobs?

Cities near Kansas City, MO with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Kansas City, MO as of August 2026, with employment types broken down into 90% Full Time, 7% Part Time, and 3% Contract. Highlights an 74% In-person, 3% Hybrid, and 23% Remote job distribution, with an average salary of $125,503 per year, or $60.3 per hour.

US E ES - Lead Data Scientist GenAI, Financial Planning & Analysis - Strategic Analytics

Deloitte

Kansas City, MO

Full-time

Re-posted 27 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 151 rated financial services


Job description

Deloitte is at the leading edge of GenAI innovation, transforming Strategic Analytics and shaping the future of Finance. We invite applications from highly skilled and experienced AI and Data Science Engineer III professionals ready to drive the development of our next-generation GenAI solutions.

Recruiting for this role ends on August 30th 2026. 

Work you'll do

As an AI and Data Science Engineer III on the Strategic Analytics team, you will be responsible for

  • Designing, developing, and deploying artificial intelligence, machine learning, and advanced analytics solutions for business stakeholders
  • Building and maintaining scalable data pipelines, application programming interfaces, and model deployment workflows in cloud environments
  • Partnering with finance, strategy, and operational teams to translate business requirements into technical solutions and actionable insights
  • Supporting the development of generative artificial intelligence use cases, prototypes, and production-ready products aligned to strategic priorities
  • Monitoring solution performance, maintaining technical documentation, and identifying opportunities to improve reliability, efficiency, and adoption

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team
Strategic Analytics is a dynamic part of the Finance Financial Planning and Analysis organization, supporting executive leaders across the firm as well as stakeholders in financial and operational functions. The team combines cloud computing, data science, artificial intelligence, strategic problem-solving, and institutional knowledge to deliver insights that inform critical business decisions and support the firm's growth.

Generative artificial intelligence is a key strategic priority for the team, with a strong focus on developing products and solutions that can create value across the organization and for clients. In this role, the selected candidate will contribute directly to high-impact initiatives that advance innovation and business transformation.

Qualifications

Required:

  • Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, Finance, or a related field
  • 4+ years of experience in data science, machine learning engineering, data engineering, or software engineering
  • 3+ years of experience developing solutions using Python
  • 2+ years of experience working with cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform
  • 2+ years of experience using Structured Query Language and working with relational or distributed data platforms
  • Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Master's degree in Computer Science, Data Science, Engineering, Statistics, or a related field
  • Experience developing generative artificial intelligence or large language model solutions
  • Experience with machine learning operations tooling and model deployment frameworks
  • Experience building application programming interfaces or production data products
  • Experience supporting finance, financial planning and analysis, or enterprise strategy use cases
  • Experience with data visualization tools such as Tableau or Power BI

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $102,500 to $188,900.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Deloitte is at the leading edge of GenAI innovation, transforming Strategic Analytics and shaping the future of Finance. We invite applications from highly skilled and experienced AI and Data Science Engineer III professionals ready to drive the development of our next-generation GenAI solutions.

Recruiting for this role ends on August 30th 2026. 

Work you'll do

As an AI and Data Science Engineer III on the Strategic Analytics team, you will be responsible for

  • Designing, developing, and deploying artificial intelligence, machine learning, and advanced analytics solutions for business stakeholders
  • Building and maintaining scalable data pipelines, application programming interfaces, and model deployment workflows in cloud environments
  • Partnering with finance, strategy, and operational teams to translate business requirements into technical solutions and actionable insights
  • Supporting the development of generative artificial intelligence use cases, prototypes, and production-ready products aligned to strategic priorities
  • Monitoring solution performance, maintaining technical documentation, and identifying opportunities to improve reliability, efficiency, and adoption

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team
Strategic Analytics is a dynamic part of the Finance Financial Planning and Analysis organization, supporting executive leaders across the firm as well as stakeholders in financial and operational functions. The team combines cloud computing, data science, artificial intelligence, strategic problem-solving, and institutional knowledge to deliver insights that inform critical business decisions and support the firm's growth.

Generative artificial intelligence is a key strategic priority for the team, with a strong focus on developing products and solutions that can create value across the organization and for clients. In this role, the selected candidate will contribute directly to high-impact initiatives that advance innovation and business transformation.

Qualifications

Required:

  • Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, Finance, or a related field
  • 4+ years of experience in data science, machine learning engineering, data engineering, or software engineering
  • 3+ years of experience developing solutions using Python
  • 2+ years of experience working with cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform
  • 2+ years of experience using Structured Query Language and working with relational or distributed data platforms
  • Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Master's degree in Computer Science, Data Science, Engineering, Statistics, or a related field
  • Experience developing generative artificial intelligence or large language model solutions
  • Experience with machine learning operations tooling and model deployment frameworks
  • Experience building application programming interfaces or production data products
  • Experience supporting finance, financial planning and analysis, or enterprise strategy use cases
  • Experience with data visualization tools such as Tableau or Power BI

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $102,500 to $188,900.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Education:Bachelor's DegreeEmployment Type:

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