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Junior Machine Learning Engineer Jobs in Missouri

Workiva

$40/hr

Implement tooling and features to support machine learning model development and deployment under the direction of a full-time Machine Learning Engineer * Help integrate tools such as LlamaIndex and ...

Workiva

$40/hr

Implement tooling and features to support machine learning model development and deployment under the direction of a full-time Machine Learning Engineer * Help integrate tools such as LlamaIndex and ...

Workiva

$40/hr

Implement tooling and features to support machine learning model development and deployment under the direction of a full-time Machine Learning Engineer * Help integrate tools such as LlamaIndex and ...

Workiva

$40/hr

Implement tooling and features to support machine learning model development and deployment under the direction of a full-time Machine Learning Engineer * Help integrate tools such as LlamaIndex and ...

Workiva

$40/hr

Implement tooling and features to support machine learning model development and deployment under the direction of a full-time Machine Learning Engineer * Help integrate tools such as LlamaIndex and ...

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All JobsMachine Learning Engineer JobsJunior Machine Learning Engineer JobsJunior Machine Learning Engineer Jobs in Missouri

Junior Machine Learning Engineer information

See Missouri salary details

$31.4K

$67.3K

$102.7K

How much do junior machine learning engineer jobs pay per year?

As of Sep 15, 2026, the average yearly pay for junior machine learning engineer in Missouri is $67,348.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,500.00 and $75,000.00 per year, depending on experience, location, and employer.

What does a junior machine learning engineer do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

What kinds of projects and responsibilities can a junior machine learning engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

What are the key skills and qualifications needed to thrive as a junior machine learning engineer, and why are they important?

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

What is the difference between Junior Machine Learning Engineer vs Data Scientist?

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
More about Junior Machine Learning Engineer jobs

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For Junior Machine Learning Engineer jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Junior Machine Learning Engineer jobs in Missouri look for?

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What cities in Missouri are hiring for Junior Machine Learning Engineer jobs?

Cities in Missouri with the most Junior Machine Learning Engineer job openings:

Junior Machine Learning Engineer jobs near you
Infographic showing various Junior Machine Learning Engineer job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $67,348 per year, or $32.4 per hour.

Lead Machine Learning Engineer, Python, GoLang, AWS

California, MO • On-site

Jobtailor
See more jobs at Jobtailorexternal

Other

Posted 3 days ago

New

Job description

  • Participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms
  • Focus on machine learning architectural design
  • Develop and review model and application code
  • Ensure high availability and performance of machine learning applications
  • Design, build, and/or deliver ML models and components that solve real-world business problems in collaboration with Product and Data Science teams
  • Inform ML infrastructure decisions using understanding of modeling techniques and issues, including model choice, data and feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation
  • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
  • Collaborate with a cross-functional Agile team to create and enhance software enabling big data and ML applications
  • Retrain, maintain, and monitor models in production
  • Leverage or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale
  • Construct optimized data pipelines to feed ML models
  • Apply continuous integration and continuous deployment practices, including test automation and monitoring
  • Ensure code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and ML follows Responsible and Explainable AI best practices
  • Continuously learn and apply the latest innovations and best practices in machine learning engineering
Requirements
  • Bachelor’s Degree
  • At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
  • At least 4 years of experience programming with Python, Scala, or Java
  • At least 2 years of experience building, scaling, and optimizing ML systems
  • Preferred: Master’s or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field
  • Preferred: 3+ years of experience building production-ready data pipelines that feed ML models
  • No agencies please
Core Competencies

Demonstrates expertise in machine learning architectural design, model development, and optimization, with a strong focus on building scalable and efficient ML systems. Proficient in leveraging cloud-based technologies and implementing best practices in responsible AI and continuous integration.

Highest-signal resume keywords
  • Machine Learning Architectural Design
  • Python Programming
  • Building Production-Ready Data Pipelines
  • Cloud-Based Architectures
  • Continuous Integration and Deployment
Hard Skills
  • Machine Learning Applications
  • Model Development
  • Data Pipeline Construction
  • Hyperparameter Tuning
  • Model Validation
  • Distributed Computing
  • Application Code Development
  • Automated Testing
  • Performance Optimization
  • Feature Selection
Soft Skills
  • Collaboration
  • Problem Solving
  • Continuous Learning
  • Cross-Functional Teamwork
  • Communication
Industry Keywords
  • Responsible AI
  • Explainable AI
  • Data-Intensive Solutions
  • Machine Learning Engineering
  • Model Governance
Tools & Technologies
  • Cloud Technologies
  • Agile Methodologies
  • ML Frameworks
  • Data Science Tools
  • Big Data Technologies
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