1

Machine Learning Engineer Jobs in Montana (NOW HIRING)

MLOps & Engineering: Implement CI/CD for machine learning (CT - Continuous Training) to ensure models remain performant in production environments. * Strategic Leadership: Partner with stakeholders ...

Algorithms, Data Analysis, Machine Learning (ML), Natural Language, Python (Programming Language), Reinforcement Learning, Researching, Scientific Writing, Statistical Models, Technical Leadership

Qualifications · Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Engineering, or related discipline. · 7-10+ years of experience in AI engineering, machine learning ...

Mentor and guide other engineers in best practices and productionizing AI technologies ... pipelines for machine learning models and the common inference APIs/SDKs and frameworks.

Mentor and guide other engineers in best practices and productionizing AI technologies ... pipelines for machine learning models and the common inference APIs/SDKs and frameworks.

... machining, & sheet metal), quality control, and concentration on cost mitigation are also core required competencies. Depending on level (I-V), Engineers progress from learning foundational ...

... machine learning, and translate emerging capabilities into actionable product opportunities. Requirements: * Bachelor's degree in computer science, engineering, data science, or a related field ...

next page

Showing results 1-20

Machine Learning Engineer information

See Montana salary details

$28.9K

$118.2K

$177.6K

How much do machine learning engineer jobs pay per year?

As of Jun 17, 2026, the average yearly pay for machine learning engineer in Montana is $118,190.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,200.00 and $142,300.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Montana? The most popular types of Machine Learning Engineer jobs in Montana are:
What are popular job titles related to Machine Learning Engineer jobs in Montana? For Machine Learning Engineer jobs in Montana, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Montana look for? The top searched job categories for Machine Learning Engineer jobs in Montana are:
What cities in Montana are hiring for Machine Learning Engineer jobs? Cities in Montana with the most Machine Learning Engineer job openings:
What are popular job titles related to Machine Learning Engineer jobs in MT? For Machine Learning Engineer jobs in MT, the most frequently searched job titles are:
Infographic showing various Machine Learning Engineer job openings in Montana as of June 2026, with employment types broken down into 100% Full Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $118,190 per year, or $56.8 per hour.
Data Scientist III - AI & Machine Learning

Data Scientist III - AI & Machine Learning

onX

Missoula, MT • On-site

Full-time

Medical, Retirement, PTO

Posted 3 days ago


Job description

ABOUT onX

We’re a team of builders, adventurers, and risk takers using technology to help people confidently explore the outdoors. Driven by our mission to awaken the adventurer inside everyone, we build products that optimize every outdoor experience and inspire confidence to get out and go further.

We’re a high-growth tech company. The pace is fast, the work takes grit, and ambiguity is part of the job. As the world changes around us, we adapt - continuously evolving how we build, prioritize, and deliver.

Our business moves quickly, and there’s real opportunity to shape what we build next. Each of our verticals - Hunt, Offroad, Backcountry, and Fish - is at a different stage of maturity, which means the challenges you encounter and the impact you have will vary depending on where you sit and what the business needs most.

We operate with an experimentation mindset, continually iterating and improving how we solve problems. We expect our people to use the latest tooling, including AI, thoughtfully and responsibly, pairing human judgment with technology to increase quality, speed, and impact.

Our impact comes to life through the products we build, in the stories of our customers, and in our growing commitment to land stewardship and recreational access.

ABOUT THIS OPPORTUNITY

We are looking for a Data Scientist who views machine learning as a product, not just a research project. You will be a foundational member of our AI team, responsible for designing, building, and deploying sophisticated models that solve complex business problems. You aren\'t just an expert in XGBoost or Transformers; you are an expert in building the pipelines that make these models reliable, scalable, and impactful.

WHAT YOU\'LL DO
Essential Job Duties & Functions
  • End-to-End Model Development: Design and implement the full ML lifecycle—from exploratory data analysis (EDA) and feature engineering to model selection, tuning, and validation.
  • GCP Architecture: Leverage the full Google Cloud AI suite (Vertex AI, BigQuery ML, Dataflow, and Pub/Sub) to build robust, cloud-native ML solutions.
  • MLOps & Engineering: Implement CI/CD for machine learning (CT - Continuous Training) to ensure models remain performant in production environments.
  • Strategic Leadership: Partner with stakeholders to translate ambiguous business challenges into technical roadmaps. Mentor junior scientists and advocate for best practices in code quality and experiment tracking.
  • Look for opportunities to embed AI as a repeatable co-pilot in daily workflows by integrating experimentation into real work, and continuously refining its use with sound judgment and validation.
WHAT YOU’LL BRING
  • 5+ years in a professional Data Science role with a track record of deploying models at scale.
  • Proficiency in Vertex AI, BigQuery, Cloud Storage, and Looker. Experience with Kubeflow is a major plus.
  • Expert-level Python (pandas, scikit-learn, PyTorch/TensorFlow), Spark, and advanced SQL.
  • Deep understanding of statistics and ML theory (e.g., Gradient Descent, Bias-Variance tradeoff, Bayesian inference).
  • Experience with ETL/ELT processes, specifically using dbt.
  • A strong curiosity for exploring new technologies, including AI
  • A shared passion for and ability to demonstrate onX’s Company Values.
  • Permanent US work authorization is a condition of employment with onX.
Our Tech Stack
  • Data Warehouse: BigQuery
  • Orchestration: Airflow (Cloud Composer)
  • Modeling: Vertex AI Pipelines, JupyterLab
  • Deployment: Docker, GKE (Google Kubernetes Engine)

Pro Tip for the Candidate: We value "clean code" as much as "smart math." If you treat your notebooks like production scripts and your Git history is a work of art, you’ll fit right in.

What Sets You Apart
  • The "Product" Mindset: You understand that a model with 99% accuracy is useless if it costs more to run than the value it creates.
  • Infrastructure as Code: You are comfortable with Terraform or similar tools to manage your cloud resources.
  • Communication: You can explain the "why" behind a complex neural network architecture to an executive without using jargon.
THE ONX EXPERIENCE

onX is a distributed company with more than 400 employees across the country. We come together regularly to work in person and stay connected through regional basecamps and a culture that balances individual ownership with deep collaboration.

While we move quickly, we’re not a scrappy start-up. We operate with clear goals, structure, and frameworks that guide how we prioritize and execute. Priorities matter. While they may shift, data shapes how we evolve as our business, products, and the world around us change.

Clear priorities and structure don’t limit ownership - they make it possible. You’ll have the autonomy to define your work and make meaningful decisions within clear strategic boundaries. You’ll partner closely with others to solve complex problems and build solutions that scale across teams and platforms. Along the way, you’ll be supported with feedback, tools, and opportunities to grow your craft as you take on new challenges.

WHERE YOU CAN WORK

onX has created a thriving distributed workforce designed to foster connection, collaboration, and shared experience across several US locations. We have two HQ locations in Bozeman and Missoula, MT and established virtual workforce Basecamps in Austin, TX; Denver, CO; Kalispell, MT; Minneapolis, MN; Portland, OR; Salt Lake City, UT; and Seattle, WA.

HOW YOU’LL BE COMPENSATED

onX is committed to compensating all employees fairly and equitably for their contributions. For this position, applicants can expect to make between $126,000 to $149,000 upon hire. The pay range will vary based on experience, skills, certifications, and education among other factors as required in the job description. In addition, full-time onX employees are eligible for a grant of common share options with a vesting schedule and a potential annual bonus of 10% based on company performance.

WHAT WE’RE OFFERING YOU
  • Competitive salaries, annual bonuses, equity, and opportunities for growth
  • Comprehensive health benefits, including a no-monthly-cost medical plan
  • Paid parental leave of 13 weeks for birthing parents and 5 weeks for non-birthing parents
  • 401k matching at 100% for the first 3% you save and 50% from 3-5%
  • Company-wide outdoor adventures and amazing outdoor industry perks
  • Annual “Get Out, Get Active” funds to fuel your active lifestyle
  • Flexible time away package that includes PTO, STO, VTO, and paid holidays
PERFORMANCE ESSENTIALS

In this role, success is driven by cognitive abilities such as concentration and problem-solving, essential for our computer-centric tasks. onX will explore reasonable accommodations to ensure that individuals with diverse abilities can fully engage in and contribute to the essential physical and mental functions of the job. If you need assistance or accommodation, please contact us at PC@onxmaps.com. 

Application Deadline is [day of week], [month] [day] at [0:00 pm] MST

Position open until filled. 

#LI-Remote

At onX, we believe that unique perspectives make us stronger. By bringing together people with different experiences, ideas, and viewpoints, we fuel innovation and move closer to our mission of awakening the adventurer in everyone. We are proud to be an equal opportunity employer and are committed to fairness not only in hiring, but also in development, compensation, and promotion. Our goal is to build an inclusive community where every team member can show up authentically and thrive. Together, we win as one team. Come join us!

onX Maps will never ask for credit card or SSN details during the initial application process. For your digital safety, apply only through our legitimate website at onXmaps.com or directly via our LinkedIn page.

onX does not sell any Personal Information, but we may transfer employment related records to our service providers or third parties that provide business services to onX or as required by law. For more information, see our Privacy Policy.

As part of our interview process, your conversation may be recorded for documentation purposes to allow interviewers to focus fully on the discussion. Recordings are confidential and accessible only to authorized personnel. Please note, onX respects all applicable laws regarding recording consent, and you will have an opportunity to opt-out if preferred.