1

Machine Learning Engineer Jobs in Wyoming (NOW HIRING)

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

next page

Showing results 1-20

Machine Learning Engineer information

See Wyoming salary details

$30.3K

$123.8K

$186K

How much do machine learning engineer jobs pay per year?

As of Jul 15, 2026, the average yearly pay for machine learning engineer in Wyoming is $123,776.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,600.00 and $149,000.00 per year, depending on experience, location, and employer.

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-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants 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 AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

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 engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

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 Wyoming? The most popular types of Machine Learning Engineer jobs in Wyoming are:
What are popular job titles related to Machine Learning Engineer jobs in Wyoming? For Machine Learning Engineer jobs in Wyoming, the most frequently searched job titles are:
What are popular job titles related to Machine Learning Engineer jobs in WY? For Machine Learning Engineer jobs in WY, the most frequently searched job titles are:
Infographic showing various Machine Learning Engineer job openings in Wyoming as of July 2026, with employment types broken down into 89% Full Time, 9% Part Time, and 2% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $123,776 per year, or $59.5 per hour.
Machine Learning Engineer

$90K - $110K/yr

Other

Posted 6 days ago


Job description

Job Title
Machine Learning Engineer
Salary
$90,000 - $110,000
Job Classification
Salaried
Location
Cheyenne, WY 82001 US
Fort Collins, CO 80527 US
Laramie, WY 82072 US (Primary)
US
Job Type
Regular
# of Hires Needed
1
Application Deadline
Job Description

Western EcoSystems Technology, Inc. (WEST) is a dynamic medium-size consulting firm with offices across the United States and Canada.We are looking for a full-time Machine Learning Engineer to join our team . WEST has a permanent core of professionals with broad experience in applied ecological studies, the sophisticated analysis of natural resource data, and impact assessment and permitting. Since its founding in 1990, the WEST team has shaped our work through our core values and key principles that our work matters to our clients, communities, and the environment. Join WEST and discover a company of passionate, committed, and highly motivated individuals.

The Machine Learning team specializes in wildlife monitoring solutions using cutting-edge technology. We develop end-to-end systems for processing and analyzing ecological data, including camera trap imagery, drone footage, and audio data. We focus on delivering practical, deployable solutions that support real-world conservation and monitoring efforts.

Example projects include:

  • Species classification and individual re-identification of wildlife from camera trap images
  • Habitat and vegetation classification from drone footage
  • Animal tracking and behavior analysis from video collar footage

Please click here to see what benefits WEST offers!

The minimum base salary for this position is $90,000 and the maximum is $110,000, plus additional annual profit-sharing bonus potential. Salary may vary based on education, knowledge, and experience.

Location is flexible, although a location in the Fort Collins, CO, Laramie, WY, or Cheyenne, WY office is preferred

Job Description

We are seeking a talented and experienced Machine Learning Engineer to join our team. In this role, you will collaborate with Machine Learning Data Scientists to train machine learning models and create robust, scalable pipelines and software tools that can be used by internal teams and external clients. Projects often involve deploying models across a variety of environments, including cloud, on-premise, and field-based systems (e.g., drones or edge devices). This role is ideal for someone who enjoys building complete solutions, working with real-world data, and solving engineering challenges in applied computer vision.

Key Responsibilities:

Machine Learning Systems & Engineering

  • Design and implement end-to-end ML pipelines, including data ingestion, preprocessing, model inference, and results delivery
  • Develop reusable software tools and workflows that support internal teams and client-facing deliverables
  • Build systems that integrate model predictions into downstream analysis, reporting, or visualization pipelines

Deployment & Productionization

  • Deploy machine learning models across diverse environments, including cloud, on-premise, and edge/field systems
  • Optimize models and pipelines for performance, reliability, and resource constraints (e.g., memory, compute, bandwidth)
  • Ensure systems are maintainable and reproducible, including versioning of data, models, and code

Data & Model Development

  • Conduct data preprocessing, QA/QC, and dataset management for ML workflows
  • Develop and evaluate computer vision models, with attention to real-world challenges such as noisy labels, class imbalance, and domain shift
  • Iterate on model and pipeline performance based on testing and deployment feedback

Collaboration & Communication

  • Collaborate with data scientists, engineers, and domain experts (e.g., ecologists, remote sensing specialists) to design effective solutions
  • Communicate technical concepts, system limitations, and results to both technical and non-technical stakeholders
  • Contribute to technical reports, project proposals, and client deliverables

Operational Ownership

  • Support debugging and monitoring of deployed systems, including identifying issues in data, models, or infrastructure
  • Contribute to team best practices around code quality, testing, and reproducibility

This is a general description of the functions for this position and is not inclusive of the duties which may be associated with this position.

Job Requirements

Qualifications :

  • Master's or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field, or Bachelor's with relevant work experience.
  • Proficient in Python and PyTorch, experience in C# preferred
  • Experience deploying ML models in resource-constrained or field environments (e.g., edge devices, drones, embedded systems)
  • Experience building user-facing tools, APIs, or automated workflows for ML systems
  • Experience with remote sensing, drone imagery, or ecological/biological datasets
  • Familiarity with cloud platforms, distributed processing, or large-scale data pipelines, especially Azure ML
  • Experience working on interdisciplinary teams involving scientists or domain experts
  • Excellent problem-solving skills and attention to detail.
  • Strong communication and collaboration skills.
  • Excellent interpersonal and human relations skills.

After an offer of employment is made, the candidate must successfully pass a pre-employment background check, drug screening, and a DMV records check that meets WEST's minimum criteria to operate a motor vehicle on behalf of the company. A valid driver's license will be required.

WEST provides equal employment opportunities to all individuals regardless of their race, color, religion, gender identity or expression, age, sex, sexual orientation, national origin, disability status, genetics, and any protected veteran status, and any other characteristic protected by federal, state or local law. Further, WEST takes affirmative action to ensure that all individuals are treated fairly, and without discrimination, for recruitment, selection, advancement and every other term and privilege associated with employment.

Education
Bachelor's Degree
Salary Grade
Exemption Type
Exempt