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Senior Machine Learning Ops Engineer Jobs in Missouri

... Ops engineer, or related position). Education Requirements Bachelor's Degree in Computer Science, Electrical Engineering, or related field required; Master's Degree preferred. Judgment / Reasoning ...

$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 ...

So what's the job As a Senior Machine Learning Data Scientist in the Data Team at Catawiki you will ... Working with cross-disciplinary teams involving product owners, developers, UX designers, and ...

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 ...

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 ...

As a Machine Learning Integration Engineer, you will help rapidly prototype, mature, and monitor ML/CV solution that are integral to Turion's Space Domain Awareness data products. You will work on ...

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Senior Machine Learning Ops Engineer information

What is a senior machine learning ops engineer?

Senior Machine Learning Ops (MLOps) Engineers are experienced professionals who design, build, and maintain the infrastructure and tools needed to deploy, monitor, and scale machine learning models in production environments. They work at the intersection of data science, software engineering, and DevOps to ensure ML models are robust, reliable, and secure. Their responsibilities often include automating model training pipelines, managing cloud resources, implementing CI/CD for ML, and ensuring model reproducibility. Senior MLOps Engineers also mentor junior staff and help define best practices for the organization’s ML workflow.

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

To thrive as a Senior Machine Learning Ops Engineer, you need expertise in machine learning, software engineering, cloud platforms, and experience with CI/CD pipelines, often supported by a computer science degree or equivalent experience. Proficiency with tools like Docker, Kubernetes, TensorFlow, PyTorch, and cloud services such as AWS, GCP, or Azure is typically required, along with familiarity with MLOps frameworks. Strong problem-solving, collaboration, and communication skills help you work effectively with cross-functional teams and manage complex ML model deployments. These skills are essential to ensure reliable, scalable, and efficient deployment of machine learning models in production environments.

What are some common challenges faced by senior machine learning ops engineers when deploying models to production?

Senior Machine Learning Ops Engineers often encounter challenges such as ensuring model reproducibility, managing model versioning, and automating deployment pipelines for scalability. Another key challenge is monitoring model performance and data drift in production, which requires robust logging and alerting systems. Collaborating closely with data scientists, software engineers, and IT teams is essential to address these challenges and maintain a stable, efficient ML infrastructure.

What is the difference between Senior Machine Learning Ops Engineer vs Data Engineer?

AspectSenior Machine Learning Ops EngineerData Engineer
CredentialsExperience with ML frameworks, cloud platforms, scripting, and DevOps toolsStrong SQL, ETL, database, and programming skills, often with cloud experience
Work EnvironmentFocus on deploying, monitoring, and maintaining ML models in productionDesigning and building data pipelines and infrastructure for data processing
Industry UsageCommon in AI/ML-focused companies, tech firms, and data-driven organizationsWidespread across industries for data management and analytics

While both roles involve working with data and cloud platforms, the Senior Machine Learning Ops Engineer specializes in deploying and maintaining machine learning models, whereas the Data Engineer focuses on building data pipelines and infrastructure. Understanding these distinctions helps in choosing the right career path or job search focus.

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

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

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

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

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

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

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

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

Infographic showing various Senior Machine Learning Ops Engineer job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 19% Part Time, and 1% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution.

Principal Machine Learning Engineer

iHerb

California, MO • On-site

$205 - $230/hr

Other

Posted 22 days ago


iHerb rating

7.5

Company rating: 7.5 out of 10

Based on 13 frontline employees who took The Breakroom Quiz


Job description

Overview

For A Better You At iHerb, we believe that living a healthy and balanced life should be easy and accessible to everyone. As a team member, we’ll empower you to live this promise each day as you make a truly global impact in your career. We strive for innovation while transforming and improving the online shopping experience for our customers. We believe that individually we are incredible, but together our growth is infinite. We are on a mission to make an impact on the global market, and the efforts of our people are paramount to helping us succeed. Whether you work in one of our logistics centers, technology hubs, corporate offices or from home, your role at iHerb will take you beyond what’s expected, turning challenge into change.

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 closely with business partners to provide machine intelligence driven solutions and products to simplify and enhance the customer experience and to automate core business processes. The Machine Learning Engineer will partner closely with Data Scientists, Applied Scientists, and Software Developers to ensure predictive models make business impact.

Responsibilities
  • Partner with the Data Platform team in a two-way exchange of best practices.
  • Adopt common patterns and build effective abstractions across different machine learning pipelines that simplify existing processes and accelerate modeling from problem inception to production deployment.
  • Develop horizontal solutions to robustly scale the team’s machine learning models and processes.
  • Build software with object-oriented design patterns and analysis (OOA and OOD) with an eye toward reducing technical debt and maintaining services at high availability.
  • Participate in requirements reviews, design reviews, and code reviews.
  • Research and prototype new technologies to support rapid business growth.
  • Interact cross-functionally with technical teams and work with data and applied scientists to identify opportunities to improve iHerb’s platform.
  • Note: This description may not cover all aspects of the role; other duties may be added as necessary.
Knowledge, Skills and Abilities
  • Required: Strong coding experience (e.g., Java, C#, Python).
  • Experience gathering data from multiple sources using big data technologies (Spark, Hadoop, BigQuery, Athena, etc.).
  • Experience building machine learning infrastructure following robust software engineering practices.
  • Knowledge of modern software development tools, systems, and practices (design patterns, CI/CD, Git, unit testing, smoke testing, integration testing, job schedulers, cloud technologies like AWS Lambda and Google Functions, etc.).
  • Exposure to all aspects of the software development life-cycle.
  • Experience with messaging technologies (Kafka, Google Pub/Sub, Kinesis, RabbitMQ, etc.).
  • Experience with Docker and Kubernetes.
  • High degree of accuracy and attention to detail; excellent organization and multitasking abilities.
Equipment Knowledge
  • Experience with Microsoft Office Suite (Word, Excel, PowerPoint).
  • Experience with Google Workspace (Gmail, Drive, Docs, Sheets, Forms) preferred.
Experience Requirements

Generally requires a minimum of two (2) years relevant experience in applied machine learning or machine learning systems/infrastructure, and one (1) year of relevant work experience in machine learning engineering or related fields (e.g., as a Machine Learning Engineer, ML Ops engineer, or related position).

Education Requirements

Bachelor’s Degree in Computer Science, Electrical Engineering, or related field required; Master’s Degree preferred.

Judgment / Reasoning

Able to identify, troubleshoot and resolve problems quickly using sound judgment and diplomacy. Ability to use judgment and reason to escalate issues as required, in a timely manner.

Physical Demands

The physical demands described are representative of those required to perform the essential functions. The team member is regularly required to talk and hear, and to sit, walk, climb stairs, use hands and fingers, bend, stoop and reach. Reaching above shoulder heights or below the waist may be required. May occasionally lift or move up to 25 pounds. Proper lifting techniques required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Work Environment

The work environment is typically moderate in noise. The environment can be hectic and fast-paced with multi-level distractions. Professional, yet casual work environment in an Office / Warehouse setting. Ability to work extended hours as required.

Compensation

The expected salary range for this role is $205,000.00 - $230,000.00 USD. The actual base pay offered will be determined by factors such as the candidate’s relevant experience, education, geographic location, and internal equity.

EEO

iHerb is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status. iHerb provides equal employment opportunities to all applicants for employment and prohibits discrimination and harassment.

Notes

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.

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What iHerb employees say

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