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Phd Computer Science Jobs in Boulder, CO (NOW HIRING)

True Anomaly

Perception Engineer

Denver, CO · On-site

Citizen and eligible for DoD Secret or TS/SCI clearance Preferred : • Master's or PhD in computer science, robotics, or a similar discipline • 2+ years of professional experience writing high ...

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Data Science Team Leader

Denver, CO · On-site

MSc or PhD in a quantitative discipline (Computer Science, Statistics, Mathematics, Engineering) or equivalent practical industry experience. * Familiarity with containerization (Docker, Kubernetes ...

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Data Science Team Leader

Denver, CO · On-site

$155K - $165K/yr

MScor PhD in a quantitative discipline (Computer Science, Statistics, Mathematics, Engineering) or equivalent practical industry experience. * Familiarity with containerization (Docker, Kubernetes ...

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Data Science Team Leader

Denver, CO

$155K - $165K/yr

MScor PhD in a quantitative discipline (Computer Science, Statistics, Mathematics, Engineering) or equivalent practical industry experience. * Familiarity with containerization (Docker, Kubernetes ...

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Data Science Team Leader

Denver, CO · On-site

$155K - $165K/yr

MSc or PhD in a quantitative discipline (Computer Science, Statistics, Mathematics, Engineering) or equivalent practical industry experience. * Familiarity with containerization (Docker, Kubernetes ...

Bet365

Senior Data Scientist

Denver, CO

MSc or PhD in a quantitative discipline (Computer Science, Statistics, Mathematics, Engineering) or equivalent practical industry experience. * Familiarity with containerization (Docker, Kubernetes ...

Capital Rx

Senior Applied AI/ML Scientist

Denver, CO · On-site

$180K - $225K/yr

PhD in AI, Machine Learning or Computer Science preferred * Minimum 4 years of experience in industry with a strong focus on applied AI/ML research and development * Strong grasp of OOP, Design ...

CACI

Staff Computer Vision AI/ML Engineer

Aurora, CO · Remote

MS or PhD in machine learning, computer science, computer vision, mathematics, or relevant fields Experience with Self-Supervised Learning (SSL) and student-teacher approaches (e.g., DINO, knowledge ...

University of Colorado

Lecturer

Denver, CO · On-site +1

$3.2K/wk

A PhD degree in computer science or related fields is required for teaching graduate level courses. A combination of a master's degree and 5 years of related experience may be substituted for the PhD.

University of Colorado

Lecturer

Denver, CO · On-site

$3.2K/wk

A combination of a bachelor's degree and 5 years of directly related experience may be substituted for the master's degree. • A PhD degree in computer science or related fields is required for ...

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Showing results 21-40

All JobsPhd Computer Science JobsPhd Computer Science Jobs in Boulder, CO

Phd Computer Science information

See Boulder, CO salary details

$58.6K

$86.2K

$101.6K

How much do phd computer science jobs pay per year?

As of Sep 6, 2026, the average yearly pay for phd computer science in Boulder, CO is $86,192.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,400.00 and $97,000.00 per year, depending on experience, location, and employer.

What is a PhD in computer science?

A PhD in Computer Science is the highest academic degree in the field, focused on advanced research and the creation of new knowledge in computing. It typically involves several years of coursework followed by original research culminating in a dissertation. Graduates often pursue careers in academia, research, or advanced industry roles that require deep technical expertise and problem-solving skills.

What are the key skills and qualifications needed to thrive as a PhD in computer science?

To thrive as a PhD in Computer Science, you need advanced expertise in algorithms, programming, and research methodologies, typically supported by a doctoral degree in computer science or a related field. Mastery of programming languages (such as Python, Java, or C++), data analysis tools, and familiarity with version control systems like Git are commonly required, along with experience in publishing academic research. Critical thinking, problem-solving, strong written and verbal communication, and perseverance are vital soft skills for success in research and collaboration. These skills and qualifications are essential for making significant contributions to the field, driving innovation, and effectively sharing knowledge with the academic and professional community.

What are some common challenges faced by PhD computer science students during their research?

PhD Computer Science students often encounter challenges such as defining a clear and impactful research problem, managing long-term projects with limited guidance, and coping with the pressure to publish in top-tier conferences or journals. Balancing coursework, teaching responsibilities, and research can also be demanding. Effective time management, networking with peers and mentors, and seeking regular feedback can help students navigate these challenges and achieve their academic goals.

Is a PhD worth it for computer science?

A PhD in computer science can lead to careers in research, academia, or specialized industry roles, often requiring advanced skills in algorithms, data analysis, and programming. While it offers opportunities for high-level positions and expertise, it typically involves several years of study and may not be necessary for most industry jobs, which often value practical experience and skills. The decision depends on career goals and the desire for research or teaching roles.

What can I do after a PhD in computer science?

A PhD in computer science prepares individuals for careers in academia, research, or advanced industry roles such as data scientist, machine learning engineer, or software architect. Graduates often pursue postdoctoral research, work in R&D departments, or obtain certifications in specialized tools and programming languages to enhance their expertise.

What jobs can I get with a PhD in computer science?

A PhD in computer science qualifies individuals for advanced roles such as research scientist, data scientist, machine learning engineer, or university professor. These positions often require strong analytical skills, programming expertise, and knowledge of algorithms, data structures, and AI tools. Graduates may work in academia, industry research labs, or technology companies focusing on innovation and development.

What are popular job titles related to Phd Computer Science jobs in Boulder, CO?

For Phd Computer Science jobs in Boulder, CO, the most frequently searched job titles are:

What job categories do people searching Phd Computer Science jobs in Boulder, CO look for?

The top searched job categories for Phd Computer Science jobs in Boulder, CO are:

What cities near Boulder, CO are hiring for Phd Computer Science jobs?

Cities near Boulder, CO with the most Phd Computer Science job openings:

Phd Computer Science jobs near you
Infographic showing various Phd Computer Science job openings in Boulder, CO as of August 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 100% In-person job distribution, with an average salary of $86,192 per year, or $41.4 per hour.

Senior Data Scientist

R2 Technologies Corporation

Denver, CO • On-site

Full-time

Re-posted 27 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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