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Senior Machine Learning Ops Engineer Jobs in Montana

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 ...

Bespoke Labs

Machine Learning Engineer

Bozeman, MT · On-site

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Great Falls, MT · On-site

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Billings, MT · On-site

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

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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 popular job titles related to Senior Machine Learning Ops Engineer jobs in Montana?

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

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

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

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

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

Senior Machine Learning Ops Engineer jobs near you
Infographic showing various Senior Machine Learning Ops Engineer job openings in Montana 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.

Summer 2027 Intern - Machine Learning Engineering

Workiva

Bozeman, MT • On-site, Remote

$40/hr

Full-time

Retirement

Posted 9 days ago

Workiva rating

9.9

Company rating: 9.9 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

1st of 247 rated software companies

Job description

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the development, deployment, and monitoring of machine learning models. Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management and Analytics organization. This is an excellent opportunity to gain hands-on experience in the machine learning lifecycle.

What You'll Do

  • Participate in discovery, requirements gathering, and prototyping of new tools and libraries
  • 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 LlamaParse into existing workflows
  • Assist in building and deploying AI Agents to automate data processing and analysis tasks
  • Participate in code reviews
  • Implement and update tests (unit, integration)
  • Track tasks and complete status updates using internal tools
  • Work in an Agile development methodology alongside your teammates

What You'll Need

Minimum Qualifications

  • Currently pursuing a bachelor’s degree or higher in Statistics, Mathematics, Computer Science, Physics, Electrical Engineering, or related field of study
  • Possess solid programming skills
  • Basic experience with source control systems such as Git

Preferred Qualifications

  • Work effectively within a geographically distributed team
  • Demonstrate strong communication and organizational skills
  • Familiarity with the data science lifecycle and basic machine learning concepts
  • Experience with containerization tools such as Docker and Kubernetes
  • Knowledge of cloud platforms such as AWS
  • Proficiency with Python and/or Go
  • Familiarity with REST APIs

Travel Requirements & Working Conditions

  • Minimal travel
  • Reliable internet access for any period of time working remotely, not in a Workiva office

Location: This internship is primarily a remote opportunity. However, if you are located near one of our office hubs, you are welcome to work in a hybrid capacity and utilize our office spaces. Check out our article on Workplace Flexibility to learn more.

When can you expect to hear back?

We are committed to attending all career fairs and recruitment events before closing our positions. That means, this position might be open without updates for a few weeks to give us time to connect with all potential candidates before wrapping up the recruitment season. Check out our tentative timeline below to see when you can expect to hear from us!

Postings close: September 27, 2026

Engineering postings close: October 2, 2026

Interviews: Early to mid October

Offers: Late October

2027 Start Dates:

This position has opportunities to start in the Spring or Summer. Please see our start dates below and let us know your availability in your application.

  • Spring 2027 Internships: Monday, January 4, 2027 (15-20 hours per week max)
  • Summer 2027 Internships: Monday, May 17, 2027 (40/hours per week max)

How You’ll Be Rewarded

Salary range in the US: $40.00 - $40.00 401(k) participation and match

Paid sick leave

A unique opportunity to further your learning experience through additional internship seasons

Why Join Workiva

Workiva is the platform designed to bring confidence, control, and a competitive edge to the world’s most complex organizations. Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation-ensuring data is trusted, traceable, and ready to act on. With an unbroken path from source to output, leaders gain confidence in their numbers, visibility into current and emerging risks, and the ability to move with speed and precision in a constantly changing world.

At Workiva, you’ll bring technology to market that executives, boards, and regulators depend on. The work you do here helps organizations navigate uncertainty, maintain trust, and make decisions that stand up to scrutiny. If you’re energized by meaningful challenges, inspired by collaborative teams, and motivated to help organizations turn uncertainty into advantage, we’d love to meet you.

Employment decisions are made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other protected characteristic.

Workiva is committed to working with and providing reasonable accommodations to applicants with disabilities. To request assistance with the application process, please email earlycareer@workiva.com .

Workiva employees are required to undergo comprehensive security and privacy training tailored to their roles, ensuring adherence to company policies and regulatory standards.

Workiva supports employees in working where they work best - either from an office or remotely from any location within their country of employment.

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