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Entry Level Machine Learning Engineer Jobs in Denver, CO

MS or PhD in machine learning, computer science, mathematics, or relevant fields * Experience leading an interdisciplinary team of researchers and software developers * Experience with any of the ...

MS or PhD in machine learning, computer science, mathematics, or relevant fields * Experience leading an interdisciplinary team of researchers and software developers * Experience with any of the ...

Senior ML Software Engineer, Watch Software

Boulder, CO · On-site

$127K - $167K/yr

We are looking for a versatile Machine Learning Software Engineer who is passionate about developing innovative, ML-driven product features that push the boundaries of sensing and human-computer ...

Job Title Civil Engineer (Entry-Level) Organizational Unit Redland -> Littleton -> LIT - Civil ... Learning & Growth goals. Responsibilities include collaborating with colleagues, taking ownership ...

ENTRY LEVEL PYTHON DEVELOPER

Boulder, CO · On-site

$53 - $73/hr

Machine learning and AI. * Deep learning. * Understanding of multi-process architecture ... data engineering experience. Benefits * On job technical support * E-verified * Help to get H1B ...

Design, build and implement machine learning models, including the development of AI Models and ... Programming and scripting languages: Python, R, C++, Julia, Javascript, SQL * API integration and ...

Responsibilities - Design and implement advanced AI and machine learning solutions - Analyze ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

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Entry Level Machine Learning Engineer information

See Denver, CO salary details

$30K

$69.3K

$117.9K

How much do entry level machine learning engineer jobs pay per year?

As of Jun 24, 2026, the average yearly pay for entry level machine learning engineer in Denver, CO is $69,275.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,400.00 and $78,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Entry Level Machine Learning Engineer position, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an Entry Level Machine Learning Engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What is an Entry Level Machine Learning Engineer job?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are the most commonly searched types of Machine Learning Engineer jobs in Denver, CO? The most popular types of Machine Learning Engineer jobs in Denver, CO are:
What are popular job titles related to Entry Level Machine Learning Engineer jobs in Denver, CO? For Entry Level Machine Learning Engineer jobs in Denver, CO, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning Engineer jobs in Denver, CO look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in Denver, CO are:
What cities near Denver, CO are hiring for Entry Level Machine Learning Engineer jobs? Cities near Denver, CO with the most Entry Level Machine Learning Engineer job openings:
Infographic showing various Entry Level Machine Learning Engineer job openings in Denver, CO as of June 2026, with employment types broken down into 14% Internship, 70% Full Time, 8% Part Time, and 8% Temporary. Highlights an 92% In-person, and 8% Remote job distribution, with an average salary of $69,275 per year, or $33.3 per hour.
AI/ML Engineer II with Security Clearance

AI/ML Engineer II with Security Clearance

Sierra Nevada Corporation

Lone Tree, CO • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 20 days ago


Sierra Nevada Corporation rating

8.6

Company rating: 8.6 out of 10

Based on 27 frontline employees who took The Breakroom Quiz

17th of 60 rated aerospace companies


Job description

The AI/ML Engineer II is a mid-level position for individuals with professional experience in designing and implementing machine learning algorithms. In this role, you will independently develop and deploy AI/ML solutions to address complex challenges, such as autonomous systems, predictive maintenance, and computer vision. You will take ownership of specific projects, perform data analysis, and optimize models for performance and scalability. This position requires a combination of technical expertise, problem-solving skills, and the ability to collaborate with multidisciplinary teams to meet mission-critical objectives. The ISR (Intelligence, Surveillance & Reconnaissance), Aviation, and Security (IAS) business area is a leader in ISR and aviation, it is a leading prime manned and unmanned aircraft systems integrator for innovative, high-performance ISR and aviation systems. Its end-to-end Command, Control, Computers, Communications and Intelligence, Surveillance & Reconnaissance (C4ISR) capabilities encompass design, integration, test, certification, ground/flight training and complete logistics support. IAS tailors solutions to customer cost, performance, and schedule requirements and designs to consistently exceed expectations - with an unrivaled record of on time and on (or under) budget deliveries. Responsibilities: * Design, implement, and optimize machine learning models for applications such as object detection, signal processing, predictive analytics, and decision-making systems.
* Develop and maintain data pipelines for collecting, preprocessing, and managing large-scale datasets. Identify data gaps and propose solutions to improve data quality.
* Conduct performance testing and validation of AI/ML models using rigorous evaluation metrics. Optimize models for accuracy, efficiency, and scalability.
* Write and deploy efficient, modular code to integrate AI/ML models into operational systems, ensuring reliability and compatibility with existing platforms.
* Test AI/ML solutions in simulated environments to evaluate performance under real-world conditions. Contribute to system-level debugging and troubleshooting.
* Collaborate with hardware engineers, software developers, and systems architects to align AI/ML solutions with mission-critical requirements.
* Document technical designs, workflows, and testing procedures for internal and external use. Share findings and best practices with team members.
* Explore and integrate emerging AI/ML frameworks, tools, and methodologies to enhance system capabilities and address new challenges.
* Train, evaluate, and optimize standard AI models (ANNs, CNNs, RNNs) for supervised and unsupervised tasks.
* Implement and test basic reinforcement learning algorithms and generative models under supervision.
* Develop and integrate signal processing and computer vision modules to enhance perception and decision-making capabilities.
* Conduct simulations and performance profiling of AI/ML models on CPU/GPU architectures, identifying bottlenecks.
* Execute validation and verification procedures, analyze test results, and support system compliance with safety and reliability standards. Qualifications You Must Have: * Bachelor's degree in computer science, mathematics, applied statistics, various engineering disciplines, or related STEM discipline
* 2+ years of experience in a related field.
* Relevant experience can be considered as a substitute for the required educational qualifications. In the absence of a degree, a minimum of 6 years of related experience is required.
* Higher level relevant degree may substitute for experience.
* Practical experience using machine learning frameworks (e.g., TensorFlow, PyTorch) and applying core AI/ML techniques, including supervised, unsupervised, and introductory reinforcement learning methods.
* Hands-on experience implementing and evaluating ANNs, CNNs, and RNNs in small-scale or pilot projects. Assisted with deploying machine learning models in production or research environments.
* Proficiency in programming languages such as Python, C++, C# or Java.
* Strong understanding of supervised and unsupervised learning techniques.
* Experience deploying AI/ML solutions in production environments. Qualifications We Prefer: * Master's degree in Artificial Intelligence, Machine Learning, or related field. Experience with reinforcement learning or generative AI models (e.g., GANs, Transformers).
* Working knowledge of Agile or DevOps practices in software/ML project environments.
* Hands-on experience with at least one advanced ML technique (e.g., clustering or dimensionality reduction) in coursework or projects.
* Basic experience with GPU programming (e.g., CUDA basics) or using GPUs for ML model training.
* Exposure to generative models (e.g., GANs, Transformers) or reinforcement learning frameworks.
* Experience analyzing and processing diverse datasets to extract insights.
* Familiarity with requirements gathering and basic deployment of ML systems.
* Awareness of hardware acceleration tools and edge AI concepts. Essential Functions: * Work extensively on a computer for coding, debugging, and integrating AI/ML systems.
* Travel occasionally to testing sites, customer locations, or conferences (up to 10-20%).
* Ability to work in a hybrid environment and manage multiple tasks effectively. This posting will be open for application for a minimum of 5 days and may be extended based on business needs. Estimated Starting Salary Range: $108,496.89 - $149,183.22. Compensation varies depending on a wide array of factors, such as candidates' key skills, relevant work experience, and education/training/certifications. The disclosed range estimate may be adjusted for any applicable geographic differential associated with the location at which the position may be filled. SNC offers a generous benefit package, including medical, dental, and vision plans, 401(k) with 150% match up to 6%, life insurance, 3 weeks paid time off, tuition reimbursement, and more . IMPORTANT NOTICE: This position requires the ability to obtain and maintain a Secret U.S. Security Clearance. U.S. Citizenship status is required as this position needs an active U.S. Security Clearance for employment. Non-U.S. citizens may not be eligible to obtain a security clearance. The Department of Defense Consolidated Adjudications Facility (DoD CAF), a federal government agency, handles the adjudicative aspects of the security clearance eligibility process for industry applicants. Adjudicative factors which affect the outcome of the eligibility determination include, but are not limited to, allegiance to the U.S., foreign influence, foreign preference, criminal conduct, security violations and illegal drug use. Learn more about the background check process for Security Clearances. SNC is a global leader in aerospace and national security committed to moving the American Dream forward. We're known and respected for our mission and execution focus, agility, and disruptive and rapid innovation. We provide leading edge technologies and transformative solutions that support our nation's most critical security needs. If you are mission-focused, thrive in collaborative environments, and want to make our country stronger with state-of-the-art technologies that safeguard freedom, join our team! SNC is an Equal Opportunity Employer committed to an environment free of discrimination. Employment decisions are made based on merit without regard to race, color, age, religion, sex, national origin, disability, status as a protected veteran or other characteristics protected by law.

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