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Graduate Machine Learning Engineer Jobs (NOW HIRING)

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

Alignerr

Machine Learning Engineer

Manhattan, NY · Remote

$50 - $70/hr

Machine Learning Engineer - AI Data Trainer Location: Remote About The Job At Alignerr, we partner with the world's leading AI research teams and labs to build and train cutting‐edge AI models.

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

Apple

Machine Learning Engineer

Austin, TX · On-site

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer ... output PhD or Graduate degree with research/work experience utilizing data science techniques ...

Quantum Machines

Machine Learning Engineer

Boston, MA · On-site

Quantum Machines is a global leader in quantum computing control systems, and they are seeking a Machine Learning Engineer to design, build, and deploy machine learning systems for quantum processors.

Compunnel

Machine Learning Engineer

Freeport, ME · Remote

Machine Learning Engineer Location: Freeport Maine Remote Must haves: * 4+ years ML experience * Python / Spark * Tensorflow / PyTorch (or similar) * Databricks * MLflow * Docker * SQL * Design and ...

Steampunk

Machine Learning Engineer

Mclean, VA · On-site +1

$115K - $150K/yr

We are looking for a more than just a "Machine Learning Engineer", but a technologist with excellent communication and customer service skills and a passion for data and problem solving.

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Graduate Machine Learning Engineer information

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$31.5K

$128.8K

$193.5K

How much do graduate machine learning engineer jobs pay per year?

As of Jun 5, 2026, the average yearly pay for graduate machine learning engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What does a Graduate Machine Learning Engineer do?

A Graduate Machine Learning Engineer is an entry-level professional who designs, develops, and tests machine learning models and algorithms. They work with data scientists and engineers to preprocess data, train models, and deploy solutions to solve real-world problems. Their responsibilities often include coding in languages like Python, using libraries such as TensorFlow or PyTorch, and staying updated with the latest advancements in machine learning. This role serves as a starting point for a career in AI, providing hands-on experience in building and optimizing intelligent systems.

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

To thrive as a Graduate Machine Learning Engineer, you need a solid foundation in computer science, mathematics (especially statistics and linear algebra), and proficiency in programming languages like Python, often supported by a relevant degree. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), version control systems (like Git), and experience with cloud platforms or data management tools are typically expected. Strong analytical thinking, problem-solving abilities, and effective communication help you collaborate and translate complex concepts into practical solutions. These skills and qualities are crucial for developing robust models, integrating them into real-world applications, and contributing effectively to multidisciplinary teams.

What are some common challenges faced by Graduate Machine Learning Engineers during their first year, and how can they overcome them?

Graduate Machine Learning Engineers often encounter challenges such as bridging the gap between academic knowledge and real-world application, working with large or messy datasets, and learning to collaborate within cross-functional teams. Adapting to production-level code standards and understanding existing codebases can also be demanding. To overcome these hurdles, it's helpful to seek mentorship from experienced colleagues, actively participate in code reviews, and invest time in learning best practices for data preprocessing and model deployment. Embracing continuous learning and open communication will ease the transition into the professional environment.

What is the difference between Graduate Machine Learning Engineer vs Data Scientist?

AspectGraduate Machine Learning EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related field; some internshipsBachelor's or Master's in Statistics, Data Science, or related field; often with experience
Work EnvironmentDeveloping ML models, coding, testing algorithmsAnalyzing data, creating visualizations, deriving insights
Employer & Industry UsageTech companies, startups, research labsFinance, healthcare, tech, consulting firms

While both roles involve working with data and algorithms, Graduate Machine Learning Engineers focus on developing and deploying machine learning models, often requiring coding and technical skills. Data Scientists analyze data to extract insights and inform decisions. The roles overlap in skills but differ in primary responsibilities and focus areas.

More about Graduate Machine Learning Engineer jobs
What cities are hiring for Graduate Machine Learning Engineer jobs? Cities with the most Graduate Machine Learning Engineer job openings:
What states have the most Graduate Machine Learning Engineer jobs? States with the most job openings for Graduate Machine Learning Engineer jobs include:
What job categories do people searching Graduate Machine Learning Engineer jobs look for? The top searched job categories for Graduate Machine Learning Engineer jobs are:
Graduate Machine Learning Engineer jobs near you
Infographic showing various Graduate Machine Learning Engineer job openings in the United States as of May 2026, with employment types broken down into 3% As Needed, 76% Full Time, 18% Part Time, and 3% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer

Waypoint Human Capital

Huntsville, AL • On-site

Other

Posted 6 days ago

Job description

Position Title: Machine Learning Engineer
Position Type: Full-time, On-Site
Location: Huntsville, AL
Clearance: Active TS
Description:
Waypoint's client is seeking a Machine Learning Engineer to support mission-critical efforts within a secure environment at the Missile and Space Intelligence Center. This role focuses on developing, integrating, and operationalizing machine learning solutions that support advanced analytics and intelligence capabilities.
The selected candidate will work across the full machine learning lifecycle, from building data pipelines and training models to deploying and monitoring production systems. This position requires a strong blend of software engineering and data science expertise, with a focus on scalability, performance, and system integration.
Responsibilities:
Integrate machine learning systems into existing software architectures and enterprise platforms
Design, build, and optimize data pipelines to support model training and inference
Develop, test, and deploy machine learning models into production environments
Manage transition from prototype to production, including deployment pipelines and monitoring solutions
Monitor model performance, including handling model drift, rollback, and failure scenarios
Conduct experiments and testing to evaluate and improve model accuracy and performance
Write clean, maintainable, and testable code in Python and related technologies
Collaborate with cross-functional teams to integrate ML capabilities into mission systems
Utilize CI/CD pipelines and GitOps practices to support automated deployment and version control
Support development in Linux and Windows environments
Required:
Active TS clearance (with ability to obtain TS/SCI with CI Polygraph)
Bachelor's degree in Computer Science, Mathematics, Statistics, Physics, or related technical field
Minimum 12+ years of overall experience, including 1-3 years working with machine learning frameworks
Strong programming skills in Python
Experience with machine learning frameworks, libraries, and data modeling techniques
Solid understanding of the machine learning lifecycle
Experience working with SQL and NoSQL databases
Experience working in Linux and Windows environments
Familiarity with CI/CD pipelines and Agile development methodologies
Understanding of software design and system integration principles
Desired:
Active TS/SCI with CI Polygraph (desired)
Experience working with large-scale (petabyte-level) datasets
Experience supporting multi-INT analytics environments
Experience deploying, monitoring, and scaling machine learning models in production
Experience with tools such as Docker, Jupyter Notebooks, PostgreSQL, GitLab, and GitHub
Experience implementing GitOps workflows
Experience working in secure or classified environment

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