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Machine Learning Engineer Jobs in Independence, MO

Indeed

Machine Learning Engineer

Kansas City, KS

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

LRS

Sr. Machine Learning Engineer

Kansas City, MO · On-site

$130K - $145K/yr

LRS Consulting is seeking a Senior Machine Learning Engineer to design, build, and scale production-grade machine learning and Generative AI systems. This role focuses on developing advanced ML and ...

Varsity Tutors

Machine Learning Tutor

Kansas City, MO · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Overland Park, KS · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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

Machine Learning Engineer information

See Independence, MO salary details

$28.7K

$117.4K

$176.4K

How much do machine learning engineer jobs pay per year?

As of Jun 11, 2026, the average yearly pay for machine learning engineer in Independence, MO is $117,405.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,500.00 and $141,300.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

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-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies 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 they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

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 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 Independence, MO? The most popular types of Machine Learning Engineer jobs in Independence, MO are:
What are popular job titles related to Machine Learning Engineer jobs in Independence, MO? For Machine Learning Engineer jobs in Independence, MO, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Independence, MO look for? The top searched job categories for Machine Learning Engineer jobs in Independence, MO are:
What cities near Independence, MO are hiring for Machine Learning Engineer jobs? Cities near Independence, MO with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Independence, MO as of June 2026, with employment types broken down into 98% Full Time, 1% Part Time, and 1% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $117,405 per year, or $56.4 per hour.
Machine Learning Engineer

Machine Learning Engineer

Indeed

Kansas City, KS

Other

Medical, PTO

Posted 25 days ago

Indeed rating

9.5

Company rating: 9.5 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

7th of 188 rated software companies

Job description

Our Mission

Our Mission

As the world's number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and creating the best experience for job seekers.

(*Comscore, Total Visits, March 2025)

Day to Day

The Machine Learning Engineer I role partners closely with business partners across various functions to help execute strategic initiatives that increase revenue, drive operational scale, and improve efficiency for continuous growth. As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source packages and research publications, and creatively adapt models for solving business problems across Indeed.

Work spans classical ML through LLM systems. You improve search and retrieval quality using real user signals. Execution includes experiments, iteration, and production reliability at scale. You collaborate with engineers, data scientists, and product teams to define problems, test approaches, and ship measurable improvements.

Responsibilities

  • Build AI/ML systems for search, ranking, and recommendations

  • Develop LLM retrieval and generation workflows

  • Improve search and ranking relevance

  • Design metrics and run experiments

  • Monitor model quality, latency, and cost

  • Debug data, models, and system issues

  • Build training, inference, and eval pipelines

Skills/Competencies

  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 2 years of related experience; or an advanced degree without experience

  • Experience building ML models in Python; solid software engineering and algorithms fundamentals

  • Experience developing backend services in Java/Kotlin for ML-driven systems and features

  • Experience writing clean, testable, and maintainable production code

  • Experience working with structured and unstructured data, including SQL for large-scale data querying, and building scalable data pipelines and features from data

  • Experience integrating ML models into search systems using engines such as OpenSearch or similar, with familiarity in container orchestration for deployment with senior guidance

  • Excellent understanding of model evaluation techniques, feature engineering, experiment design, and familiarity with LLM systems (RAG, embeddings, output evaluation)

Salary Range Transparency

Tier 1 - United States of America 118,000 - 176,000 USD per year

Tier 2 - United States of America 130,000 - 196,000 USD per year

Tier 3 - United States of America 143,000 - 215,000 USD per year

Tier 4 - N/A

Tier 5 - United States of America 163,000 - 245,000 USD per year

Salary Range Disclaimer

The salary range for this role reflects the minimum and maximum compensation for the role. Offers are typically made between the range minimum and the range midpoint. Actual compensation will be determined based on job-related skills, experience, and expertise, as evaluated during the interview process. The range(s) listed is just one component of Indeed's total compensation package for employees. Other rewards may include quarterly bonuses, Restricted Stock Units (RSUs), a Paid Time Off policy, and many region-specific benefits. Compensation may also vary based on where a role is performed, as work locations are grouped into geographic pay tiers to reflect cost of labor differences in different geographic markets. Candidates can view geographic pay tiers by location on our career site (https://www.indeed.com/careers/paytiers), and recruiters can confirm how location is considered for a specific role.

Benefits - Health, Work/Life Harmony, & Wellbeing

Indeed is deeply committed to building a workplace and global community where inclusion is not only valued, but prioritized. We're proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, family status, marital status, sexual orientation, national origin, genetics, neuro-diversity, disability, age, or veteran status, or any other non-merit based or legally protected grounds.

Indeed provides reasonable accommodations to qualified individuals with disabilities in the employment application process. To request an accommodation, please visit https://www.indeed.com/careers/accommodations. If you are requesting accommodation for an interview, please reach out at least one week in advance of your interview.

For more information about our commitment to equal opportunity/affirmative action, please visit our Careers page (https://www.indeed.com/careers).

Equal Opportunities and Accommodations Statement

Inclusion and belonging are fundamental to our hiring practices and company culture, forming an integral part of our vision for a better world of work. At Indeed, we're committed to the wellbeing of our employees and on a mission to make this the best place to work and thrive. We believe that fostering an inclusive environment where every employee feels respected and accepted benefits everyone, fueling innovation and creativity.

We value diverse experiences, including those who have had prior contact with the criminal legal system. We are committed to providing individuals with criminal records, including formerly incarcerated individuals, a fair chance at employment.

Those with military experience are encouraged to apply. Equivalent expertise demonstrated through a combination of work experience, training, military experience, or education is welcome.

Indeed's Employee Recruiting Privacy Policy

Like other employers Indeed uses our own technologies to help us find and attract top talent from around the world. In addition to our site's user and privacy policy found at https://www.indeed.com/legal, we also want to make you aware of our recruitment specific privacy policy found at https://www.indeed.com/legal/indeed-jobs.

Agency Disclaimer

Indeed does not pay placement fees for unsolicited resumes or referrals from non-candidates, including search firms, staffing agencies, professional recruiters, fee-based referral services, and recruiting agencies (each individually, an "Agency"), subject to local laws. An Agency seeking a placement fee must obtain advance written approval from Indeed's internal Talent Acquisition team and execute a fee agreement with Indeed for each job opening before making a referral or submitting a resume for that opening.

AI Notice

Indeed is committed to ensuring fairness and transparency throughout our hiring process. We use artificial intelligence (AI) tools to assist in the screening, assessment, and selection of applicants for this position by analyzing information provided in resumes and applications. Our use of AI does not replace human decision-making.

Unless otherwise notified, Indeed does not use AI constituting an AEDT or an ADMT as those tools are defined in applicable laws.

The deadline to apply to this position is 6/12/2026. Job postings may be extended at the hiring team's discretion based on applicant volume.

Reference ID: 46644

Reference ID: 46644

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