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Machine Learning Data Associate Jobs in Colorado

Cymertek

Data Scientist

Aurora, CO · On-site

Data Scientist LOCATION Aurora, CO 80014 CLEARANCE TS/SCI Full Poly (Please note this position ... In this role, you will use advanced analytics, machine learning models, and statistical methods to ...

Cymertek

Data Scientist

Aurora, CO

Data Scientist LOCATIONAurora, CO 80014 CLEARANCETS/SCI Full Poly (Please note this position ... In this role, you will use advanced analytics, machine learning models, and statistical methods to ...

Synergistic it

AI & Machine Learning Engineer

Denver, CO

$117.90K - $141.50K/yr

... data scientist , and machine learning/AI engineer . In other words, SynergisticIT focuses on ... building candidates across Java / Full Stack / DevOps and Data Analytics / Data Engineering / Data ...

Synergistic it

AI & Machine Learning Engineer

Denver, CO

$117.90K - $141.50K/yr

... data scientist , and machine learning/AI engineer . In other words, SynergisticIT focuses on ... building candidates across Java / Full Stack / DevOps and Data Analytics / Data Engineering / Data ...

AppFolio

CO

$264K - $330K/yr

Improve the standards for end-to-end ML systems: data collection, model training, evaluation ... D. in Computer Science, Machine Learning, or a related field (required). * 10+ years of experience ...

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$10

$19

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How much do machine learning data associate jobs pay per hour?

As of May 29, 2026, the average hourly pay for machine learning data associate in Colorado is $19.70, according to ZipRecruiter salary data. Most workers in this role earn between $16.15 and $20.96 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Data Associate, and why are they important?

To thrive as a Machine Learning Data Associate, you need strong analytical skills, attention to detail, and a basic understanding of data annotation and labeling processes, often supported by a degree in computer science or a related field. Familiarity with data management tools, annotation platforms, and sometimes scripting languages like Python is typically required. Strong communication, collaboration, and problem-solving abilities help you work efficiently with data science teams and ensure high-quality outcomes. These skills and qualities are crucial for producing accurate datasets that directly impact the effectiveness of machine learning models.

How does a Machine Learning Data Associate typically collaborate with data scientists and engineers within a project team?

As a Machine Learning Data Associate, you play a vital role in supporting data scientists and engineers by annotating, cleaning, and organizing large datasets to ensure high data quality. You'll frequently communicate with team members to clarify labeling guidelines, provide feedback on data inconsistencies, and report any edge cases encountered during annotation. This collaboration ensures that the datasets used for training machine learning models are accurate and comprehensive, directly impacting the success of the project. Expect regular team meetings and ongoing feedback loops to maintain alignment with evolving project requirements.

What are Machine Learning Data Associates?

Machine Learning Data Associates are professionals who support the development of machine learning models by preparing, labeling, and validating data sets. Their work ensures that data used for training algorithms is accurate, consistent, and properly annotated. They may also assist with data cleaning, quality checks, and sometimes basic data analysis tasks. This role is crucial in industries where high-quality labeled data is essential for building effective AI systems.

What is the difference between Machine Learning Data Associate vs Data Analyst?

AspectMachine Learning Data AssociateData Analyst
Required SkillsData cleaning, labeling, basic programming, understanding of ML workflowsData interpretation, visualization, statistical analysis
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing, healthcare sectors
Common CertificationsData Science certifications, Python, SQLExcel, Tableau, SQL certifications

The main difference is that Machine Learning Data Associates focus on preparing and labeling data specifically for machine learning models, while Data Analysts interpret data to generate insights for business decisions. Both roles require strong data skills and often overlap, but their primary objectives and work environments differ.

What cities in Colorado are hiring for Machine Learning Data Associate jobs? Cities in Colorado with the most Machine Learning Data Associate job openings:
Machine Learning Data Associate jobs near you
Infographic showing various Machine Learning Data Associate job openings in Colorado as of May 2026, with employment types broken down into 76% Full Time, 23% Part Time, and 1% Contract. Highlights an 96% Physical, 3% Hybrid, and 1% Remote job distribution, with an average salary of $40,982 per year, or $19.7 per hour.
Applied Machine Learning Engineer

Applied Machine Learning Engineer

The Aerospace Corporation

Colorado Springs, CO • On-site

Full-time

Posted 3 days ago

Job description

Job Summary:
The Aerospace Corporation is the trusted partner to the nation’s space programs, solving the hardest problems and providing unmatched technical expertise. They are seeking a Machine Learning Engineer to join their Data Science and Artificial Intelligence Department, focusing on developing AI and data-enabled tools for national security and commercial customers.
Responsibilities:
• DSAID applies data science and AI knowledge across the space enterprise, to Aerospace enterprise capabilities, and towards corporate workforce development and strategic focus areas
• Machine Learning Engineers learn and develop their skills by working on teams spanning disciplines, experience levels, and organizational boundaries.
• Primary functions include:
• Evaluation of technologies for use in scalable and resilient mission-critical applications in a production environment
• Coordinated development and execution of AI/ML experiments
• Coordinated development of proof-of-concept infrastructure configuration and software prototypes
• Collaboration with small, innovative teams to deliver features and products
• Written and verbal presentation of results to team members and stakeholders
• Reinforcing an environment of learning and progress with team members and others
• Focus on accountability and innovation in leadership competency development
• Duties, responsibilities and activities may change, or new ones may be assigned as needed
• Machine learning engineers must maintain a commitment to ongoing learning in order to stay current with government missions and the ever-changing climate of data science and AI. This requires both ongoing education in relevant domains, such as physics, math, and/or computer science, as well as an understanding of the existing systems and future objectives of government missions.
Qualifications:
Required:
• Bachelors degree in Computer Science, Computer Information Systems, Electrical or Computer Engineering or related technical field(s)
• 5 or more years of experience in Data Scientist or Machine Learning Engineer or AI/ML Researcher role in any domain
• Strong proficiency in at least two different programming languages (e.g. Python, R, C/C++)
• Experience with ML frameworks and familiarity with common libraries used for Data Science and Machine Learning, such as pandas, pytorch or JAX.
• Experience with on and off-policy reinforcement learning algorithms such as Deep Q Learning, A3C, and PPO.
• Working knowledge of fundamental graph theory and graph neural networks.
• Hands on experience with container orchestration tooling (Docker, Kubernetes, etc.)
• Experience with and understanding of software engineering concepts with an AI focus (MLOps/DevOps, ML Development Lifecycle, data structures, etc.)
• Working knowledge of Unix/Linux operating systems
• This position requires ability to obtain and maintain a security clearance, which is issued by the US government. U.S citizenship is required to obtain a security clearance.
Preferred:
• 8 or more years of experience in Data Scientist or Machine Learning Engineer or AI/ML Researcher role in any domain
• Demonstrated experience architecting, designing, or implementing enterprise-scale AI/ML solutions with multiple tenants and cloud integration
• Experience leading technical teams and in mentoring junior staff.
• Familiarity with data pipelining and streaming technologies (Apache Kafka, temporal, etc.)
• Advanced degree in Computer Science, Computer Information Systems, Electrical or Computer Engineering, or related field(s)
• Publications in reinforcement learning, graph theory, or a relevant AI/ML domain.
• Experience in designing or managing enterprise-level ML platforms and production-grade ML models at scale
• Familiarity with High Performance Computing hardware for ML (GPUs, TPUs), CUDA programming, and advanced ML optimization techniques and architectures
• Demonstrated ability to exercise judgement and critical thinking in a scientific discipline
• Experience implementing and guiding teams toward software development best practices
• Experience in SQL, NoSQL, Cypher and other big data querying languages
• Demonstrated contributions to open-source software repositories (github, kaggle, etc.)
• Experience deploying ML models on cloud platforms (AWS, Azure, etc.)
• Domain expertise relevant to one or more customer organization mission areas (USSF, NRO, etc.)
• Active security clearance
Company:
As the government’s preeminent space innovation partner, Aerospace brings technical expertise to advance the nation's missions in space. Founded in 1960, the company is headquartered in El Segundo, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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