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Applied Machine Learning Intern Jobs in Boulder, CO

SciTec

Senior Staff / Senior Machine Learning Engineer

Boulder, CO · On-site

$108K - $148K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The ideal candidate is a strong individual contributor with deep experience in machine learning, highthroughput data processing, and applied algorithmic development. Success in this role requires ...

SciTec

Senior Staff / Senior Machine Learning Engineer

Boulder, CO · On-site

$128K - $170K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The ideal candidate is a strong individual contributor with deep experience in machine learning, high-throughput data processing, and applied algorithmic development. Success in this role requires ...

SciTec

Senior Staff / Senior Machine Learning Engineer

Boulder, CO · On-site

$128K - $170K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The ideal candidate is a strong individual contributor with deep experience in machine learning, high-throughput data processing, and applied algorithmic development. Success in this role requires ...

SciTec

Senior Staff / Senior Machine Learning Engineer

Boulder, CO · On-site

$110K - $151K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The ideal candidate is a strong individual contributor with deep experience in machine learning, high‑throughput data processing, and applied algorithmic development. Success in this role requires ...

Thaloz

CO - Sr. Data Scientist - 229

Denver, CO · On-site

Mentor and support team members through pairing, feedback, and sharing best practices. * 5+ years of professional experience in data science, applied machine learning, or a related quantitative role.

General Motors

Staff Machine Learning Engineer - Mapping

Denver, CO · On-site

$185 - $335/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Role We are looking for a Staff Machine Learning Engineer to serve as a technical leader for ... applied to mapping problems. * Own cross‑functional technical initiatives, working closely with ...

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Showing results 21-40

All JobsApplied Machine Learning Intern JobsApplied Machine Learning Intern Jobs in Boulder, CO

Applied Machine Learning Intern information

See Boulder, CO salary details

$26.4K

$44.2K

$91.3K

How much do applied machine learning intern jobs pay per year?

As of Aug 20, 2026, the average yearly pay for applied machine learning intern in Boulder, CO is $44,163.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,700.00 and $47,700.00 per year, depending on experience, location, and employer.

What is the difference between Applied Machine Learning Intern vs Data Science Intern?

AspectApplied Machine Learning InternData Science Intern
Required SkillsMachine learning algorithms, programming (Python, R), data analysisStatistical analysis, data visualization, programming (Python, R)
Work EnvironmentDeveloping ML models, experimenting with algorithms, deploying modelsData cleaning, analysis, reporting insights
Industry UsageTech companies, AI startups, research labsBusiness analytics, market research, finance

Applied Machine Learning Interns focus on developing and deploying machine learning models, requiring knowledge of algorithms and programming. Data Science Interns typically handle data analysis, visualization, and reporting. While both roles involve data skills, applied ML interns work more on model implementation, whereas data science interns focus on insights and data interpretation.

What are popular job titles related to Applied Machine Learning Intern jobs in Boulder, CO?

For Applied Machine Learning Intern jobs in Boulder, CO, the most frequently searched job titles are:

What job categories do people searching Applied Machine Learning Intern jobs in Boulder, CO look for?

The top searched job categories for Applied Machine Learning Intern jobs in Boulder, CO are:

What cities near Boulder, CO are hiring for Applied Machine Learning Intern jobs?

Cities near Boulder, CO with the most Applied Machine Learning Intern job openings:

Applied Machine Learning Intern jobs near you
Infographic showing various Applied Machine Learning Intern job openings in Boulder, CO as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $44,163 per year, or $21.2 per hour.

Senior Data Scientist

R2 Technologies Corporation

Denver, CO • On-site

Full-time

Re-posted 10 days ago

Job description

Overview:
Job Title: Senior Data Scientist - Knowledge Domain: Product (Job ID: 2099)
Location: Work From Home - USA, Denver, Colorado 80237 - look for locals
Duration: July 15, 2025 - February 27, 2026
Company: Western Union
Hire Type: Contractor (Contract Only)
Standard Hours per Week: 40
JOB DESCRIPTION
Senior Data Scientist - Knowledge Domain: Product
We are seeking a technically advanced and product-oriented Senior Data Scientist to lead the development of machine learning and deep learning solutions that power intelligent decision-making and innovative products. This role is ideal for someone with extensive experience in building, evaluating, and deploying ML and neural network models in production environments. You'll collaborate cross-functionally to create and scale real-world AI applications that have direct impact on users and business performance.
Role Responsibilities:
Design, build, and evaluate machine learning and deep learning models for classification, regression, recommendation, NLP, computer vision, and time-series forecasting.
Apply deep learning techniques (e.g., CNNs, RNNs, LSTMs, Transformers) to solve complex, data-intensive problems.
Lead the development of ML products, from model prototyping through production deployment, performance monitoring, and continuous improvement.
Select appropriate architectures and hyperparameters, optimize model performance, and use proper evaluation metrics (e.g., AUC, F1, BLEU, IoU, perplexity) based on the use case.
Collaborate with product managers and engineers to translate business challenges into deployable solutions using AI/ML.
Design automated pipelines for data preprocessing, feature engineering, training, and inference (batch or real-time).
Evaluate model drift, monitor performance post-deployment, and implement retraining pipelines as part of a production MLOps system.
Mentor junior data scientists, contribute to code reviews, and lead technical discussions across the data science and engineering teams.
Role Requirements:
Bachelor's degree in Computer Science, Statistics, Applied Math, or related field (Master's or PhD strongly preferred).
5+ years of industry experience in applied machine learning, with 2+ years focused on deep learning and neural network applications.
Experience in Banking, Payments or Financial Services formulating AI data solutions that allow us to leverage our data to know our customers better and target our resources for better market penetration and focused attention and education.
Proficiency in Python and ML libraries such as scikit-learn, XGBoost, TensorFlow, Keras, or PyTorch.
Deep understanding of neural networks, model regularization, overfitting/underfitting prevention, and GPU-accelerated training.
Experience with customer data enrichments.
Proven track record of building, evaluating, and deploying machine learning models at scale in production environments.
Experience with cloud platforms (AWS/GCP/Azure), containerization, and model serving technologies.
Excellent communication skills, with the ability to present complex findings to both technical and non-technical stakeholders.
Hands-on experience with real-world applications of deep learning, such as recommendation engines, fraud detection, customer segmentation, document summarization, image recognition, or speech processing.
Familiarity with MLOps tools (e.g., MLflow, SageMaker, Airflow, Kubeflow).
Experience with CI/CD for ML, feature stores, and real-time inference systems.
Contributions to academic research, open-source ML projects, or ML/AI patents.
Skills:
Knowledge Domain

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