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Apprentice Machine Learning Testing Jobs in Wyoming

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

Machinist (Shop)

Gillette, WY

$21.75 - $29.50/hr

Entrance testing to determine knowledge, aptitude, and suitability for the position. * Must be able ... Employee learning and development programs Diversity & Inclusion Commitment At Komatsu, we come ...

Machinist (Shop)

Gillette, WY · On-site

$22.25 - $30.50/hr

Entrance testing to determine knowledge, aptitude, and suitability for the position. * Must be able ... Employee learning and development programs Diversity & Inclusion Commitment At Komatsu, we come ...

Machinist (Shop)

Gillette, WY · On-site

$22.25 - $30.50/hr

Entrance testing to determine knowledge, aptitude, and suitability for the position. * Must be able ... Employee learning and development programs Diversity & Inclusion Commitment At Komatsu, we come ...

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Apprentice Machine Learning Testing information

What kinds of projects or tasks can I expect to work on as an apprentice machine learning testing?

As an Apprentice Machine Learning Testing, you’ll typically assist in evaluating machine learning models by designing and running tests, analyzing model outputs, and helping identify issues like bias or overfitting. You may work closely with data scientists and software engineers to validate model performance and ensure results align with project objectives. Your daily tasks might include preparing test datasets, executing automated testing scripts, and documenting findings to help improve model reliability. This role often serves as a valuable introduction to practical machine learning workflows and quality assurance processes in technical teams.

What are the key skills and qualifications needed to thrive as an apprentice machine learning testing, and why are they important?

To thrive as an Apprentice in Machine Learning Testing, a foundational understanding of statistics, programming (especially Python), and basic machine learning concepts is essential, often supported by a degree or coursework in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, Jupyter Notebooks, and version control systems is typically required. Strong analytical thinking, attention to detail, and effective communication skills help apprentices collaborate and identify testing issues efficiently. These skills ensure accurate model validation, effective troubleshooting, and contribute to the robust deployment of machine learning solutions.

What does an apprentice machine learning testing do?

An Apprentice Machine Learning Testing professional assists in evaluating and validating machine learning models to ensure they perform as expected. They typically work under the guidance of experienced data scientists or engineers, running tests, analyzing results, and helping to identify issues such as bias or inaccuracies in algorithms. Their responsibilities may also include developing test cases, writing reports, and learning about data preprocessing and evaluation metrics. This role is ideal for those who are new to the field and want to build foundational skills in machine learning quality assurance.

What is the difference between Apprentice Machine Learning Testing vs Machine Learning Engineer?

AspectApprentice Machine Learning TestingMachine Learning Engineer
Required CredentialsBasic understanding of ML concepts, often pursuing relevant certifications or degreesAdvanced degrees (BSc, MSc, PhD) in CS or related fields, with extensive experience
Work EnvironmentEntry-level, supervised testing environments, often in training programsFull-time, independent development and deployment of ML models in production
Employer & Industry UsageInternships, training programs, entry-level roles in tech companiesEstablished tech firms, startups, research institutions

Apprentice Machine Learning Testing roles focus on learning and assisting with testing ML models under supervision, while Machine Learning Engineers design, build, and deploy ML systems independently. The apprentice position is ideal for gaining foundational skills, whereas the engineer role requires advanced expertise and experience.

What are popular job titles related to Apprentice Machine Learning Testing jobs in Wyoming? For Apprentice Machine Learning Testing jobs in Wyoming, the most frequently searched job titles are:
What job categories do people searching Apprentice Machine Learning Testing jobs in Wyoming look for? The top searched job categories for Apprentice Machine Learning Testing jobs in Wyoming are:
What cities in Wyoming are hiring for Apprentice Machine Learning Testing jobs? Cities in Wyoming with the most Apprentice Machine Learning Testing job openings:

$90 - $110/hr

Other

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

Machine Learning Engineer

$90,000 - $110,000

Location: Fort Collins, CO; Laramie, WY; or Cheyenne, WY (flexible)

Overview

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, sophisticated analysis of natural resource data, and impact assessment and permitting. Since its founding in 1990, the WEST team has shaped our work through its 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
  • 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

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.

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
  • 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
  • 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
  • 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
  • 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.

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.

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