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Aviation Machine Learning Jobs (NOW HIRING)

Tagup

Machine Learning Engineer

Salt Lake City, UT · On-site

We are seeking a Machine Learning Engineer to join our Salt Lake City team and help shape the next generation of AI-driven defense and aviation systems, focusing on designing, deploying, and scaling ...

Tagup

Machine Learning Engineer

Manhattan, NY · On-site

We are seeking a Machine Learning Engineer to join our Salt Lake City team and help shape the next generation of AI-driven defense and aviation systems by designing, deploying, and scaling AI ...

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How much do aviation machine learning jobs pay per hour?

As of Jun 4, 2026, the average hourly pay for aviation machine learning in the United States is $22.82, according to ZipRecruiter salary data. Most workers in this role earn between $19.71 and $25.48 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in Aviation Machine Learning, and why are they important?

To thrive in Aviation Machine Learning, you need strong expertise in machine learning, data analysis, and a background in aerospace engineering or computer science, often with an advanced degree. Familiarity with programming languages (such as Python), machine learning frameworks (like TensorFlow or PyTorch), and aviation-specific simulation tools is typically required. Excellent problem-solving abilities, attention to detail, and effective communication skills help bridge technical solutions with operational aviation needs. These skills are vital for developing reliable, safe, and innovative AI solutions that enhance efficiency and safety in the aviation industry.

How does an Aviation Machine Learning specialist typically collaborate with other teams within an airline or aerospace company?

Aviation Machine Learning specialists often work closely with cross-functional teams, including software engineers, data scientists, aviation operations experts, and maintenance crews. Collaboration is essential for integrating machine learning models into flight operations, predictive maintenance, and safety systems. Specialists frequently participate in meetings to align project goals, share data insights, and ensure their solutions meet regulatory and operational standards. This collaborative environment not only drives innovation but also provides opportunities for continuous learning and career development.

What is aviation machine learning?

Aviation machine learning refers to the application of machine learning techniques and artificial intelligence in the aviation industry. These technologies are used to improve flight safety, optimize operations, predict maintenance needs, and enhance passenger experiences. Machine learning models can analyze large amounts of data from aircraft, air traffic, and weather to assist in decision-making and automation. By leveraging these tools, airlines and manufacturers can reduce costs, increase efficiency, and minimize risks.

What is the difference between Aviation Machine Learning vs Aircraft Data Analyst?

AspectAviation Machine LearningAircraft Data Analyst
Required CredentialsDegree in Data Science, Computer Science, or related field; knowledge of ML frameworksDegree in Aviation, Data Analysis, or related field; proficiency in data tools
Work EnvironmentTech-focused teams, R&D departments, aviation tech companiesAirlines, maintenance organizations, aviation service providers
Industry UsageDeveloping predictive models for flight optimization, safety, and maintenanceAnalyzing aircraft performance data, maintenance logs, and operational metrics

While both roles involve data analysis within the aviation industry, Aviation Machine Learning focuses on developing machine learning models to improve safety and efficiency, whereas Aircraft Data Analysts interpret aircraft data to support maintenance and operational decisions. The roles often overlap but differ in technical scope and application.

Infographic showing various Aviation Machine Learning job openings in the United States as of May 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution, with an average salary of $47,468 per year, or $22.8 per hour.
Machine Learning Engineer

Machine Learning Engineer

Tagup

Salt Lake City, UT • On-site

Full-time

Posted 17 days ago

Job description

Job Summary:
Tagup is a defense technology company founded at MIT that is delivering logistics decision advantage with next-generation AI. We are seeking a Machine Learning Engineer to join our Salt Lake City team and help shape the next generation of AI-driven defense and aviation systems, focusing on designing, deploying, and scaling AI solutions for mission-critical operations.
Responsibilities:
• Develop, train, and optimize ML models for large-scale applications.
• Build pipelines for data ingestion and model deployment.
• Work with engineers and subject-matter experts to refine solutions.
• Conduct testing and validation to ensure reliability.
• Co-author technical reports on data analysis and model performance.
• Continuously improve ML infrastructure and workflows.
• Collaborate with customers to identify new data sources and the industrial processes they will support; some customer travel may be required.
Qualifications:
Required:
• 4+ years of machine learning experience, with strong Python skills and proficiency in frameworks such as PyTorch or TensorFlow.
• Proven ability to deploy ML models into production and work with large, complex datasets.
• Hands-on experience with MLOps tools and practices, including Kubernetes, MLflow, and CI/CD pipelines.
• Experience building and managing cloud infrastructure as code (AWS, Azure, or GCP) with tools such as Terraform or Ansible.
• Familiarity with datastores (MySQL, Postgres, or MongoDB) and prior exposure to aviation, defense, or other safety-critical environments is a plus.
Company:
Tagup provides asset management decision support, lowering the cost of in-service failures, business interruption, and equipment breakdown. Founded in 2015, the company is headquartered in Somerville, USA, with a team of 11-50 employees. The company is currently Early Stage.

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