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Mlops Engineer Jobs in Missouri (NOW HIRING)

Jobtailor

Staff AI Software Engineer

California, MO · On-site

$150 - $200/hr

Familiarity with DevOps/DevSecOps/MLOps concepts * Proficient in Python, C++, and Java * Familiarity with Linux-based operating systems * Demonstrated ability to work independently * Experience with ...

New

iHerb

Sr. Software Engineer II - AI

California, MO · On-site

$200 - $250/hr

Exposure to MLOps tooling or model deployment pipelines. * Contributions to internal developer tooling, golden path standards, or SDLC process improvements. * Experience with e-commerce platforms ...

Equifax, Inc.

AI Engineer

Saint Louis, MO · On-site

Champion MLOps for Agentic Systems: Establish and lead best practices for the reliability ... Define and report on key engineering metrics (SLA, SLO, SLI) and ensure compliance with security ...

MasterCard

Senior AI Platform Engineer (DevOps)

O Fallon, MO

$121K - $156K/yr

You will work at the intersection of platform engineering, cloud infrastructure, MLOps, and AI operations to deliver enterprise-grade capabilities that enable teams to safely develop, deploy, observe ...

iHerb

Principal Engineer - AI Platform

California, MO · On-site

$200 - $250/hr

MLOps experience: model deployment, monitoring, lifecycle management, and cost governance in a ... engineering experience, with a significant portion at senior, staff, or principal IC level.

Bass Pro Shops

Lead Engineer AI/ML - Onsite

Springfield, MO · On-site

$93K - $122K/yr

Partner with MLOps / Cloud ML Engineering to package, register, deploy, monitor, and optimize models in cloud, edge, or hybrid environments. * Evaluate and select model architectures, pretrained ...

Equifax, Inc.

AI Engineer

Saint Louis, MO · On-site

$150 - $200/hr

Champion MLOps for Agentic Systems: Establish and lead best practices for the reliability ... Define and report on key engineering metrics (SLA, SLO, SLI) and ensure compliance with security ...

Bass Pro Shops

Lead Engineer AI/ML - Onsite

Springfield, MO · On-site

$93K - $122K/yr

Partner with MLOps / Cloud ML Engineering to package, register, deploy, monitor, and optimize models in cloud, edge, or hybrid environments. * Evaluate and select model architectures, pretrained ...

Boeing

Senior Data Engineer

Hazelwood, MO

$100K - $135K/yr

Senior Data Engineer Company: The Boeing Company Boeing Defense, Space & Security (BDS) is hiring a ... Experience with MLOps and MLOps tool stack such as ClearML or MLFlow * Experience working in cloud ...

Boeing

Senior Data Engineer

Hazelwood, MO · On-site

$100K - $135K/yr

Senior Data Engineer Company: The Boeing Company Boeing Defense, Space & Security (BDS) is hiring a ... Experience with MLOps and MLOps tool stack such as ClearML or MLFlow * Experience working in cloud ...

Boeing

Senior Data Engineer

Hazelwood, MO · On-site

$100K - $135K/yr

Senior Data Engineer Company: The Boeing Company Boeing Defense, Space & Security (BDS) is hiring a ... Experience with MLOps and MLOps tool stack such as ClearML or MLFlow * Experience working in cloud ...

ClickUp

Senior AI Engineer - AI Platform

California, MO · On-site

$125 - $150/hr

Stay current with advancements in AI infrastructure, MLOps, and LLM applications, and proactively ... Deep expertise in backend engineering, distributed systems, and cloud‑native technologies (e.g ...

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Showing results 21-40

All JobsMlops Engineer JobsMlops Engineer Jobs in Missouri

Mlops Engineer information

What is an MLOps engineer?

An MLOps Engineer is responsible for deploying, monitoring, and maintaining machine learning models in production. They bridge the gap between data science and operations by automating workflows, optimizing infrastructure, and ensuring model reliability. Their role includes CI/CD for ML models, data pipeline management, and performance monitoring. They also work with cloud platforms, containerization, and orchestration tools to scale ML systems efficiently.

What are some common challenges MLOps engineers face in their daily work?

Mlops Engineers often encounter challenges in integrating new machine learning models into existing production systems while ensuring minimal downtime and maintaining data integrity. Managing the scaling and orchestration of models across various cloud or on-prem environments can be complex, requiring close coordination with data scientists and DevOps teams. Staying up to date with rapidly evolving tools and best practices is also essential in this field. Addressing these challenges provides valuable opportunities to innovate and improve both technical processes and team collaboration.

What are the key skills and qualifications needed to thrive as an MLOps engineer, and why are they important?

To thrive as an Mlops Engineer, you need strong skills in software engineering, machine learning pipelines, and cloud infrastructure, often backed by a degree in computer science, engineering, or a related field. Familiarity with tools such as Docker, Kubernetes, TensorFlow, AWS/GCP/Azure, and CI/CD systems is essential, and certifications like AWS Certified Machine Learning or Kubernetes Administrator are often valued. Effective communication, problem-solving, and teamwork are crucial soft skills for collaborating across data science and IT teams. These abilities enable Mlops Engineers to efficiently deploy, manage, and scale machine learning models in dynamic production environments.

What do you need to be a MLOps engineer?

To become a MLOps engineer, you typically need a strong background in software engineering, machine learning, and cloud platforms. Proficiency in programming languages like Python, experience with containerization tools such as Docker, and knowledge of CI/CD pipelines are essential. Certifications in cloud services and familiarity with tools like Kubernetes and ML frameworks also enhance qualifications.

Who earns more, ML engineer or MLOps engineer?

MLOps engineers typically earn slightly more than ML engineers due to their focus on deploying, maintaining, and scaling machine learning systems, which requires expertise in cloud platforms, automation, and infrastructure. Salary differences can vary based on experience, location, and company size, but MLOps roles often command higher compensation because of their specialized skill set.

What are the most commonly searched types of Mlops Engineer jobs in Missouri?

The most popular types of Mlops Engineer jobs in Missouri are:

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

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

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

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

Mlops Engineer jobs near you
Infographic showing various Mlops Engineer job openings in Missouri as of August 2026, with employment types broken down into 89% Full Time, 8% Part Time, and 3% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution.

Staff AI Software Engineer

Jobtailor

California, MO • On-site

$150 - $200/hr

Other

Posted 3 days ago

New

Job description

  • Design, develop, document, test, debug, and deploy state-of-the-art AI/ML applications
  • Collaborate with AI/ML and software engineers
  • Collaborate with cross-functional teams to deploy AI/ML solutions in development and production environments
  • Design and develop requirements for software development and software testing environments
  • Develop sustainable quality products
  • Support advanced AI capabilities including LLMs, NLP, NLU, NLG, AI-based decision-making, sensor fusion, data fusion, computer vision, and image processing
Requirements
  • Bachelor's Degree in Computer Science or a STEM discipline from an accredited university with 12 years of experience; OR Master's Degree with 10 years of experience; OR PhD Degree with 8 years of experience
  • Experience with AI models and algorithms, including LLMs, DNN, genetic algorithms, embedding models, or deep learning
  • Experience using and deploying AI LLM tools, including coding assistants, infrastructure, or similar tools
  • Experience working in large code bases containing multiple languages, such as monorepos
  • Experience developing requirements and working with software in integration, requirements verification, and testing environments
  • Ability to carry out rapid prototyping and proof-of-concept demonstrations
  • Understanding of software engineering best practices, including source control and software architecture
  • Active US Government Secret clearance with a background investigation within the past 6 years or enrollment in Continuous Evaluation
  • U.S. Citizenship required for positions with a government clearance
  • Familiarity with AI models and their limitations
  • Familiarity with DevOps/DevSecOps/MLOps concepts
  • Proficient in Python, C++, and Java
  • Familiarity with Linux-based operating systems
  • Demonstrated ability to work independently
  • Experience with LLMs, including prompt engineering, LLM development frameworks, fine tuning, or quantization
  • Ability to obtain and maintain US Government Top Secret clearance
  • Robust history of research excellence, such as peer-reviewed publications or significant contributions to open-source ML libraries
Core Competencies

Demonstrates expertise in designing and developing AI/ML applications, with a strong focus on LLMs, NLP, and software engineering best practices. Proven ability to collaborate across teams and deliver high-quality, sustainable AI solutions in both development and production environments.

Highest-signal resume keywords
  • AI/ML Application Development
  • Experience with LLMs and Deep Learning
  • Proficient in Python, C++, and Java
  • Active US Government Secret Clearance
  • Familiarity with DevOps/DevSecOps/MLOps
ATS Optimization Keywords Hard Skills
  • AI Models and Algorithms
  • Software Development Requirements
  • Software Testing Environments
  • Rapid Prototyping
  • Source Control Best Practices
  • Prompt Engineering
  • LLM Development Frameworks
  • Fine Tuning
  • Quantization
  • Integration and Verification
Soft Skills
  • Ability to Work Independently
  • Collaboration with Cross-Functional Teams
Certifications & Qualifications
  • Bachelor's Degree in Computer Science or STEM
  • Master's Degree in Computer Science or STEM
  • PhD in Computer Science or STEM
Industry Keywords
  • AI-Based Decision-Making
  • Sensor Fusion
  • Data Fusion
  • Computer Vision
  • Image Processing
Tools & Technologies
  • AI LLM Tools
  • Linux-Based Operating Systems
  • Infrastructure for AI Tools
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