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Junior Machine Learning Jobs in Missouri (NOW HIRING)

Jobtailor

Lead Machine Learning Engineer

California, MO · On-site

$140 - $210/hr

Proficiency in technical mentorship of junior and mid-level engineers * Willingness to learn ... Machine Learning * Natural Language Processing * LLM-Based Systems * Software Architecture * Model ...

Third-Party Job Posts

As a Staff Machine Learning Engineer , you will play a key role in building and implementing ... Leadership: Demonstrated ability to influence cross-functional teams, mentor junior talent, and ...

Walmart

Principal, Data Scientist (Pricing)

Noel, MO · On-site

$110K - $220K/yr

You will work closely with data scientists, machine learning engineers, operations research ... Mentor junior team members and provide guidance on technical and methodological aspects of pricing ...

Walmart

Principal, Data Scientist (Pricing)

Cassville, MO · On-site

$110K - $220K/yr

You will work closely with data scientists, machine learning engineers, operations research ... Mentor junior team members and provide guidance on technical and methodological aspects of pricing ...

Walmart

Principal, Data Scientist (Pricing)

Anderson, MO · On-site

$110K - $220K/yr

You will work closely with data scientists, machine learning engineers, operations research ... Mentor junior team members and provide guidance on technical and methodological aspects of pricing ...

Jobtailor

AI/ML Software Engineer

California, MO · On-site

$95 - $135/hr

Work independently with some guidance, and review or guide activities of more junior employees ... Bachelor's degree in a STEM field Core Competencies Demonstrates expertise in Machine Learning ...

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Junior Machine Learning information

What does a junior machine learning engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

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

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.

What types of projects and tasks can a junior machine learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

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

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

What are the most commonly searched types of Machine Learning jobs in Missouri?

The most popular types of Machine Learning jobs in Missouri are:

What are popular job titles related to Junior Machine Learning jobs in Missouri?

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

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

The top searched job categories for Junior Machine Learning jobs in Missouri are:

Junior Machine Learning jobs near you
Infographic showing various Junior Machine Learning job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer 727

Freedom Technology Solutions Group

Saint Louis, MO • On-site

Full-time

Re-posted 2 days ago

Job description

Freedom Technology Solutions Group is seeking a Machine Learning Engineer to develop, deploy, and optimize production AI/ML capabilities supporting mission-critical geospatial and intelligence systems. You will work at the intersection of software engineering, cloud architecture, and data science to build scalable machine learning pipelines capable of operating within secure government environments.

This is a hands-on engineering position focused on moving models from research into reliable production systems.


Responsibilities:

  • Da
  • Design, train, validate, and deploy machine learning models
  • Build production inference pipelines
  • Develop feature engineering workflows
  • Optimize model performance and resource utilization
  • Implement MLOps pipelines supporting continuous integration and deployment
  • Build scalable APIs exposing AI capabilities
  • Monitor model drift and operational performance
  • Collaborate with Data Scientists and Software Engineers
  • Deploy AI workloads into AWS cloud environments
  • Support computer vision, NLP, and geospatial AI initiatives
  • Collaborate with architects, data scientists, and mission stakeholders to gather, document, and refine customer requirements, including data mapping and integration needs
  • Assist in implementing integration solutions in collaboration with development team members
  • Facilitate communication between stakeholders to ensure timely and effective requirements execution
  • Ensure activities align with established processes, standards, and mission objectives
  • Contribute to documentation of processes, procedures, integration patterns, and lessons learned


Key Technologies

  •  A
  • Python
  • PyTorch
  • TensorFlow
  • Scikit-learn
  • Hugging Face
  • MLflow
  • Docker/Podman
  • Kubernetes/EKS
  • ECS
  • Lambda
  • SageMaker
  • GitLab CI/CD
  • Linux
  • PostgreSQL/PostGIS, Aurora, Oracle (w/Spatial)
  • Redis, Elasticache
  • GDAL, Rasterio, OGR

Required Qualifications

  • Active TS/SCI clearance (eligible for CI Poly)
  • 1-3(Junior), 3-7(Journeyman), 8-11 (Senior), >12 (Principal) years of experience in software development, system integration, or technical support roles
  • Experience working directly with customers or stakeholders in a technical or mission environment
  • Strong communication and coordination skills across technical and non-technical teams
  • Experience gathering and documenting requirements
  • Ability to manage multiple tasks and priorities in a dynamic environment
  • Familiarity with Agile development practices
  • Experience using GitLab or similar tools for collaboration and tracking


Desired Qualifications

  • Experience deploying production AI systems
  • Experience with computer vision
  • Experience with large language models
  • Geospatial AI experience
  • AWS AI services
  • Experience processing satellite imagery
  • Familiarity secure data movement environments
  • Experience working with enterprise service processes such as Service+
  • Development or scripting experience (Python, JavaScript, or similar)
  • Geospatial/GIS development a plus
  • Experience with data mapping or integration workflows (using JSON or other object notation)
  • Familiarity with operational dashboards and metrics reporting
  • Experience supporting customer requirement implementation and/or system integration efforts

Apply