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Mlops Machine Learning Engineer Jobs in Missouri

Jobtailor

Machine Learning Engineer II

California, MO · On-site

$120 - $180/hr

Exposure to MLOps practices, including model deployment, monitoring, retraining, and CI/CD for ML ... Machine Learning Engineering * Python or Java Proficiency * MLOps Practices * Distributed Data ...

Kohl's

$95K - $131K/yr

Contribute to the roadmap for Machine Learning Engineering and Data Science tools, including ... Experience in MLOps or DevOps practices, including building and operating production ML systems ...

Jobtailor

Machine Learning Engineer

California, MO · On-site

$130 - $190/hr

PhD in STEM +0 years of relevant experience or equivalent related work experience * 5+ years of experience in data engineering, machine learning engineering, or related roles * Data Pipeline ...

6AM City, LLC

Machine Learning Engineer

California, MO · On-site

$110 - $170/hr

As a Machine Learning Integration Engineer, you will help rapidly prototype, mature, and monitor ML ... Contribute to the deployment of MLOps processes and techniques * Assist in the development of ...

iHerb

Principal Machine Learning Engineer

California, MO · On-site

$205 - $230/hr

Job Summary The Machine Learning Engineer will tackle challenging problems and create scalable machine learning systems and platforms that make an impact on millions of users. This role will work ...

Codinix Consulting Services

MLOps Engineer

California, MO · On-site

$120 - $150/hr

Develop and maintain robust machine learning pipelines using frameworks such as MLflow, Kubeflow ... AI/ML and MLOps . * Strong programming experience in Python and Java , along with SQL and ML ...

Bass Pro Shops

Lead Engineer AI/ML - Onsite

Springfield, MO · On-site

$93K - $122K/yr

The Machine Learning Engineer designs, builds, tests, and optimizes machine learning systems that ... Partner with MLOps / Cloud ML Engineering to package, register, deploy, monitor, and optimize ...

Jobgether

$80K - $110K/yr

Our partner is looking for a Senior Geospatial Machine Learning Engineer based in Netherlands. Join a fully remote, mission-driven climate technology environment where machine learning and satellite ...

Walmart

Staff, Machine Learning Engineer

Anderson, MO · On-site

$130K - $260K/yr

We are looking for a strong Staff Machine Learning Engineer who has the passion to develop AI driven intelligent products for the Associate Productivity and Experience team, with the ability to ...

Walmart

Staff, Machine Learning Engineer

Noel, MO · On-site

$130K - $260K/yr

We are looking for a strong Staff Machine Learning Engineer who has the passion to develop AI driven intelligent products for the Associate Productivity and Experience team, with the ability to ...

Walmart

Staff, Machine Learning Engineer

Cassville, MO · On-site

$130K - $260K/yr

We are looking for a strong Staff Machine Learning Engineer who has the passion to develop AI driven intelligent products for the Associate Productivity and Experience team, with the ability to ...

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Mlops Machine Learning Engineer information

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

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

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.

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

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

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

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

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

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

Mlops Machine Learning Engineer jobs near you
Infographic showing various Mlops 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.

Machine Learning Engineer II

California, MO • On-site

Jobtailor
See more jobs at Jobtailorexternal

$120 - $180/hr

Other

Posted 5 days ago

Job description

  • Build batch and real-time ML pipelines for ad delivery, ranking, bidding, and optimization
  • Deploy and integrate ML models into low-latency ad delivery and campaign systems
  • Develop and maintain data pipelines for large-scale impression, click, and conversion data
  • Create reusable ML components, APIs, and workflows to support experimentation and iteration
  • Ensure reliability, scalability, and performance through monitoring and continuous optimization
  • Analyze data to improve models, features, and business outcomes
  • Collaborate with product, engineering, and analytics teams to deliver marketplace impact
  • Apply software engineering best practices and support responsible use of AI/ML
  • Own and deliver ML components or services within cross-functional teams
  • Mentor others and help set technical direction and engineering standards
Requirements
  • Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience
  • 2+ years of industry experience in machine learning engineering, including model development and production deployment
  • Proficiency in Python or Java
  • Experience using machine learning frameworks
  • Solid software engineering fundamentals
  • Proven ability to own and deliver ML components or services within cross-functional teams
  • Familiarity with real-time or near-real-time ML systems and production operations
  • Experience operating production ML systems at scale, including monitoring, troubleshooting, and iterative improvement
  • Familiarity with distributed data processing, including Spark and Databricks
  • Familiarity with cloud platforms, preferably AWS
  • Exposure to MLOps practices, including model deployment, monitoring, retraining, and CI/CD for ML
  • Experience building or experimenting with ranking, prediction, classification, recommendation, or NLP models
  • Experience designing APIs, data pipelines, and data models for ML-powered applications
  • Interest or background in advertising, marketplaces, e-commerce, or travel platforms
  • Awareness of responsible and secure AI/ML practices in production environments
  • Employees must be able to work in the office at least three days a week
  • No relocation assistance is available
Core Competencies

Demonstrates expertise in building and deploying machine learning pipelines, with a strong foundation in software engineering principles and experience in real-time ML systems. Capable of collaborating across teams to enhance model performance and business outcomes while adhering to responsible AI/ML practices.

Highest-signal resume keywords
  • Machine Learning Engineering
  • Python or Java Proficiency
  • MLOps Practices
  • Distributed Data Processing
  • Cloud Platforms (AWS)
ATS Optimization KeywordsHard Skills
  • Machine Learning Frameworks
  • Data Pipeline Development
  • API Design
  • Model Deployment
  • Monitoring and Troubleshooting
  • Ranking Models
  • Prediction Models
  • Classification Models
  • Recommendation Models
  • Natural Language Processing (NLP)
Soft Skills
  • Collaboration
  • Mentoring
  • Technical Direction
Industry Keywords
  • Advertising
  • Marketplaces
  • E-commerce
  • Travel Platforms
Tools & Technologies
  • Spark
  • Databricks
  • AWS
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