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$63.5K

$147.5K

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How much do ai ml software engineer jobs pay per year?

As of Jul 6, 2026, the average yearly pay for ai ml software engineer in the United States is $147,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $173,000.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior AI/ML software engineers with extensive experience, advanced skills in deep learning, and proficiency in tools like TensorFlow or PyTorch can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Achieving this level often requires a combination of technical expertise, leadership roles, and sometimes stock options or bonuses.

What are some common challenges AI/ML Software Engineers face when deploying machine learning models to production?

AI/ML Software Engineers often encounter challenges such as ensuring model scalability, managing data pipelines, and maintaining model performance over time. Transitioning from prototype to production requires close collaboration with DevOps and data engineering teams to integrate models into existing systems. Additionally, monitoring models for drift and retraining them with new data is crucial to ensure they continue delivering accurate results. Addressing these challenges effectively requires solid software engineering practices and a proactive approach to cross-functional teamwork.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position such as a senior AI/ML engineer or research scientist with extensive experience, advanced skills in machine learning frameworks, and often leadership responsibilities. Such roles usually require a strong educational background, specialized certifications, and may include bonuses or stock options that contribute to the total compensation. These positions are rare and generally found in large tech companies or innovative startups at the forefront of AI development.

Are AI ML engineers in demand?

AI ML engineers are in high demand due to the rapid growth of artificial intelligence and machine learning applications across industries. Companies seek professionals skilled in programming, data analysis, and frameworks like TensorFlow or PyTorch to develop and deploy AI solutions, leading to strong job growth and competitive salaries in this field.

How much do AI ML engineers get paid?

AI ML software engineers typically earn between $80,000 and $150,000 annually, with salaries increasing for those with advanced skills, certifications, or experience in specialized tools like TensorFlow or PyTorch. Entry-level positions may start lower, while senior roles or those in high-demand industries can pay significantly more.

What are the key skills and qualifications needed to thrive as an AI/ML Software Engineer, and why are they important?

To thrive as an AI/ML Software Engineer, you need a strong foundation in computer science, mathematics (especially statistics and linear algebra), and proficiency in programming languages such as Python or Java, often supported by a relevant degree. Experience with machine learning frameworks (like TensorFlow or PyTorch), cloud platforms, and familiarity with data management tools or certifications in AI/ML are typically required. Critical thinking, problem-solving, and effective communication are essential soft skills for collaborating on complex projects and explaining technical concepts. These skills and qualities are vital to successfully design, develop, and deploy intelligent systems that solve real-world problems.

What is the difference between Ai Ml Software Engineer vs Data Scientist?

AspectAi Ml Software EngineerData Scientist
Required SkillsProgramming, machine learning, software developmentStatistics, data analysis, programming
Work EnvironmentSoftware development teams, tech companiesResearch labs, analytics teams
Common CertificationsMachine Learning certifications, programming coursesData Science certifications, statistical courses
Industry UsageAI product development, software solutionsData analysis, predictive modeling

While both roles involve working with data and machine learning, Ai Ml Software Engineers focus on developing and deploying AI applications and software, whereas Data Scientists primarily analyze data to extract insights and build models. The roles often overlap but differ in their core focus and daily tasks.

What are AI/ML Software Engineers?

AI/ML Software Engineers are professionals who design, develop, and implement artificial intelligence (AI) and machine learning (ML) models and systems. They work with large datasets, build algorithms, and use programming languages such as Python or Java to create intelligent applications. Their responsibilities often include data preprocessing, model training, evaluation, and deployment. AI/ML Software Engineers collaborate with data scientists and other engineers to integrate machine learning capabilities into software products. They are essential in fields like healthcare, finance, and technology, where AI-driven solutions are increasingly important.
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Ai Ml Software Engineer jobs near you
Infographic showing various Ai Ml Software Engineer job openings in the United States as of June 2026, with employment types broken down into 70% Full Time, 10% Part Time, and 20% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $147,524 per year, or $70.9 per hour.
AI/ML Software Engineer

AI/ML Software Engineer

Frontier Technology Inc.

Chesapeake, VA • On-site, Remote

Full-time

Posted 18 days ago

Job description

Overview
FTI Defense is seeking an AI/ML Software Engineer to design, build, and deploy secure, scalable software and data systems that support mission operations, analytics, and simulation environments. This role is for a hands-on engineer and someone who loves writing code, building systems end-to-end, and solving real-world technical challenges in secure, distributed environments.
FTI Defense delivers mission-focused solutions to the Department of Defense (DoD/DoW) and Intelligence Community (IC) through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges by integrating people, process, and technology.
Responsibilities
Software Design & Development
  • Design and implement APIs, data pipelines, and simulation runtime logic that connect and enable mission applications.
  • Develop software using modern programming languages such as Java, Python, C++, or TypeScript/Angular.
  • Write clean, testable, and maintainable code following secure coding and software engineering best practices.
  • Build and integrate modular microservices to improve scalability, maintainability, and interoperability.

Cloud & Containerized Environments
  • Build and deploy containerized, cloud-native services using Docker, Kubernetes, and CI/CD pipelines (GitLab, Jenkins, or equivalent).
  • Implement Infrastructure-as-Code and automation scripts to accelerate deployment and configuration management.
  • Contribute to secure deployments across hybrid or disconnected environments (IL4-IL6, AWS GovCloud, or on-prem).

Systems Integration & Distributed Computing
  • Develop distributed systems and data integration frameworks using message buses such as Kafka or Redis.
  • Engineer data flow between analytic, AI, and simulation components to support real-time mission use cases.
  • Collaborate with system engineers and architects to ensure interoperability across software ecosystems.

Data & Analytics Integration
  • Build and manage databases (PostgreSQL, MongoDB, graph DBs) and model complex data relationships.
  • Develop data services that feed analytics pipelines or integrate AI/ML outputs into runtime systems.
  • Work with serialization and exchange formats such as JSON, Protobuf, GeoJSON, or KML.

Security, Testing & Sustainment
  • Write, test, and deploy software within secure or classified environments.
  • Automate testing and monitoring to ensure performance, reliability, and repeatable deployments.
  • Support the transition of prototypes to operational systems, focusing on maintainability and observability.

Education/Qualifications
Minimum Requirements:
  • Must be a U.S. citizen and be willing to obtain and maintain a security clearance, as needed.
  • 6-10+ years of professional software engineering experience.
  • 3+ years of professional experience with DevSecOps, Zero-Trust, or ATO/RMF processes in Department of Defense (DoD/DoW) environments.
  • Strong full-stack or systems engineering background.
  • Proficiency in one or more of the following languages: Java, Python, C++, or TypeScript/Angular.
  • Experience building containerized, cloud-native solutions using Docker, Kubernetes, and CI/CD pipelines.
  • Complete understanding of distributed systems and message buses (Kafka, Redis, etc.).
  • Experience developing or integrating analytics and AI models into production systems.

Preferred Qualifications:
  • Experience deploying code in IL4-IL6 or edge/disconnected environments.
  • Familiarity with databases such as PostgreSQL, MongoDB, or graph databases.
  • Knowledge of Infrastructure-as-Code (Terraform, CloudFormation, or CDK).
  • Bachelor's degree in Computer Science, Software Engineering, or a related technical field.
  • Active Secret clearance preferred; ability to obtain one is required.

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