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Full Stack Machine Learning Engineer Jobs (NOW HIRING)

General Atomics

Machine Learning Engineer

Poway, CA · On-site

... the team's autonomy stack. * Maintains the strict confidentiality of sensitive information ... May substitute equivalent machine learning engineer experience in lieu of education. * Must have an ...

Aqua IT

Machine Learning Engineer

Springfield, VA · On-site

Develop and maintain full-stack applications while ensuring operational excellence and reliability ... of machine learning/statistical modeling data analysis tools and techniques Preferred ...

Forhyre

Machine Learning Engineer

New York, NY

We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...

Cymertek

Machine Learning Engineer

Aurora, CO · On-site

Machine Learning Engineer LOCATION Aurora, CO 80014 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

Workday

Machine Learning Engineer

Pleasanton, CA

$127K - $153K/yr

... stacks to enable training, deployment, and lifecycle management of a variety of ML models ... This includes the full machine learning life cycle - data processing, model fine-tuning, model ...

New

Workday, Inc.

Machine Learning Engineer

Pleasanton, CA · On-site

$127K - $153K/yr

... stacks to enable training, deployment, and lifecycle management of a variety of ML models ... This includes the full machine learning life cycle - data processing, model fine-tuning, model ...

New

Cymertek

Machine Learning Engineer

Honolulu, HI · On-site

Machine Learning Engineer LOCATION Honolulu, HI 96815 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative ...

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

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Full Stack Machine Learning Engineer information

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$44.5K

$134.8K

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How much do full stack machine learning engineer jobs pay per year?

As of Sep 14, 2026, the average yearly pay for full stack machine learning engineer in the United States is $134,771.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $158,000.00 per year, depending on experience, location, and employer.

What is a full stack machine learning engineer?

A Full Stack Machine Learning Engineer is responsible for designing, developing, and deploying machine learning models into production. They work across the entire ML pipeline, from data collection and preprocessing to model training, evaluation, and deployment using backend and frontend technologies. This role requires expertise in software engineering, data engineering, and machine learning frameworks like TensorFlow or PyTorch. Additionally, they ensure scalability, reliability, and maintainability of ML systems in real-world applications.

What are the key skills and qualifications needed to thrive as a full stack machine learning engineer?

To thrive as a Full Stack Machine Learning Engineer, you need robust programming skills (Python, JavaScript), a deep understanding of machine learning algorithms, and experience with both backend and frontend development. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (AWS, Azure, GCP), and tools such as Docker and Kubernetes, as well as relevant certifications, are highly beneficial. Strong problem-solving abilities, effective communication, and a collaborative mindset are essential soft skills for working across interdisciplinary teams. These competencies are crucial to designing, deploying, and scaling machine learning solutions in production environments while ensuring seamless integration from data to user interface.

What are some typical challenges full stack machine learning engineers face, and how do they overcome them?

Full Stack Machine Learning Engineers often encounter challenges such as integrating complex machine learning models into scalable and maintainable production systems, and ensuring efficiency across both backend and frontend components. They must address issues like managing large and varied datasets, optimizing model inference times, and adapting to fast-evolving technologies. Overcoming these hurdles often requires close collaboration with data scientists, DevOps professionals, and product teams, as well as staying updated with best practices in MLOps and system architecture. Being proactive in learning new tools and fostering effective communication are key strategies for success in this dynamic role.

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Full Stack Machine Learning Engineer jobs near you
Infographic showing various Full Stack Machine Learning Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution, with an average salary of $134,771 per year, or $64.8 per hour.

Machine Learning Engineer

Poway, CA • On-site

General Atomics
Space Research Administration • 10K+ employees
Learn more about General Atomicsexternal

Full-time

Re-posted 22 hours ago

Key responsibilities

  • Develops and communicates insights and algorithms related to machine learning and statistical modeling.

  • Uses programming languages and technologies to translate algorithms and technical specifications into code, perform testing, debugging, and complete documentation.

  • Interfaces with external vendors and partners to integrate their technology into the team's autonomy stack.

General Atomics rating

9.0

Company rating: 9.0 out of 10

Based on 39 frontline employees who took The Breakroom Quiz

Job description

Job Summary
General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of General Atomics, is a world leader in proven, reliable remotely piloted aircraft and tactical reconnaissance radars, as well as advanced high-resolution surveillance systems.
We have an exciting opportunity for a Machine Learning Engineer in Poway, CA. The Autonomy and Artificial Intelligence Solutions Software group is charted to develop and deploy end-to-end autonomous systems that enable unmanned aerial systems (UAS) to execute autonomous missions.
DUTIES AND RESPONSIBILITIES:
  • Develops and communicates descriptive, diagnostic, predictive and prescriptive insights/algorithms of limited scope.
  • In product/systems improvement projects, uses machine language and statistical modeling techniques to include but not limited to decision trees, logistic regression, Bayesian analysis and others to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy.
  • In both theoretical development environments and specific product design, implementation and improvement environments, uses programming language and technologies to translate algorithms and technical specifications into code.
  • Completes programming and implements efficiencies, performs testing and debugging.
  • Completes documentation and procedures for installation and maintenance.
  • Applies deep learning technologies to give computers the capability to visualize, learn and respond to situations of limited scope.
  • Lead technical teams and scope challenging projects into executable sprints.
  • Drive code reviews to help team adhere to general DevSecOps and MLOps best practices.
  • Have a growth mindset and be comfortable in a setting where milestones shift often due to customer preferences or technology evolution.
  • Adapts machine learning to areas such as virtual reality, augmented reality, artificial intelligence, robotics and other products that allow users to have an interactive experience.
  • Interface with external vendors and partners to integrate their technology into the team's autonomy stack.
  • Maintains the strict confidentiality of sensitive information.
  • Performs other duties as assigned.
  • Responsible for observing all laws, regulations and other applicable obligations wherever and whenever business is conducted on behalf of the Company. Expected to work in a safe manner in accordance with established operating procedures and practices.
We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply.
Job Qualifications
  • Typically requires a bachelors or master's degree in computer science, engineering, mathematics, or a related technical discipline from an accredited institution and two or more years of machine learning experience with a bachelors degree. May substitute equivalent machine learning engineer experience in lieu of education.
  • Must have an understanding of machine learning concepts, principles, and theory.
  • Demonstrates the ability to follow and apply advanced machine learning knowledge, adapt cutting edge standard techniques, and utilize the required diagnostics, tools and equipment, while ensuring safety and regulatory compliance.
  • Experience in developing and leading scalable software architectures from scratch.
  • Experience in optimizing AI models to meet edge processing requirements.
  • Strong coding skills in Java, Java Script, C/C++, Python
  • Experience in AI frameworks such as Tensorflow and pyTorch.
  • Excellent verbal and written communication skills.
  • Must be able to architect, design, and develop complex software.
  • Technical expertise in the application of engineering principles, concepts, theory, and practice as well as project management and leadership skills including organizing, planning, scheduling, and coordinating workloads to meet established deadlines or milestones.
  • Active membership and participation in relevant conference and professional society organizations.
  • Demonstrated recent history of academic quality publications in the area of AI/ML and autonomy.
  • Must be able to understand new concepts quickly and apply them accurately throughout an evolving environment.
  • Strong communication, computer, and interpersonal skills are required to enable an effective interface with other professionals, to produce appropriate documentation, and to present results to a limited internal audience.
  • Must be able to work both independently and on a team.
  • Able to work extended hours as required.
  • Customer focused, must be able to work on a self-initiated basis and in a team environment, and able to work extended hours and travel as required.
  • Ability to obtain and maintain a DoD security clearance is required.

What General Atomics employees say

Pay

Benefits

Hours and flexibility

Workplace

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About General Atomics

Sourced by ZipRecruiter

General Atomics (GA), and its affiliated companies, is one of the world's leading resources for high-technology systems development ranging from the nuclear fuel cycle to remotely piloted aircraft, airborne sensors, and advanced electric, electronic, wireless and laser technologies.

Industry

Space research administration

Company size

10,000+ Employees

Headquarters location

San Diego, CA, US

Year founded

1955

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