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Internship Full Stack Machine Learning Engineer Jobs in Queens, NY

Goodfire

Machine Learning Engineer

Manhattan, NY · On-site

They are seeking Machine Learning Engineers to build a platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to the development of core technology and ...

ExaCare AI

Machine Learning Engineer

Manhattan, NY · On-site

$110 - $150/hr

We are seeking a highly adaptable, creative, and well‑rounded Machine Learning Engineer to join our team. You will own the end‑to‑end ML lifecycle, from dataset creation and foundational ...

Zenlaw

Full-Stack Engineer (Remote)

New York, NY · On-site +1

As a Zenlaw Full-Stack Engineer you will: * Develop new features working with cross-functional ... Python (machine learning, Natural Language Processing, string manipulation) You care about:

Fox

Machine Learning Engineer I

New York, NY · Hybrid

$74K - $130K/yr

ABOUT THE ROLE As a Machine Learning Engineer in FOX Forward Deployed, you will rotate across two ... Experience building and evaluating models through coursework, research, projects, internships

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All JobsFull Stack Machine Learning Engineer JobsInternship Full Stack Machine Learning Engineer JobsInternship Full Stack Machine Learning Engineer Jobs in Queens, NY

Internship Full Stack Machine Learning Engineer information

See Queens, NY salary details

$46.4K

$140.6K

$198.8K

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

As of Aug 9, 2026, the average yearly pay for internship full stack machine learning engineer in Queens, NY is $140,628.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,800.00 and $164,900.00 per year, depending on experience, location, and employer.

What skills and qualifications are needed to thrive as an internship full stack machine learning engineer?

To succeed as an Internship Full Stack Machine Learning Engineer, you need a solid understanding of programming (Python, JavaScript), basic machine learning concepts, and foundational knowledge in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, web development tools (React, Node.js), and version control systems like Git is typically expected. Strong problem-solving abilities, collaboration skills, and a willingness to learn set exceptional interns apart. These skills enable interns to contribute effectively to both model development and deployment, bridging the gap between data science and software engineering in real-world applications.

What is an internship full stack machine learning engineer?

An Internship Full Stack Machine Learning Engineer is a student or early-career professional who supports both the development of machine learning models and the integration of these models into full-stack applications. This role typically involves working on data preprocessing, building and training machine learning algorithms, and deploying these models within web or mobile applications. Interns in this field gain experience in both backend and frontend technologies, as well as in machine learning frameworks and tools. The position is ideal for those seeking hands-on experience in applying AI solutions within real-world products.

What do internship full stack machine learning engineers do?

As an Internship Full Stack Machine Learning Engineer, you can expect to work on end-to-end machine learning projects that involve both model development and integration into web or cloud applications. This may include tasks like cleaning and preparing datasets, building and testing machine learning models, developing APIs to serve predictions, and collaborating with front-end developers to deliver user-facing features. Interns often work closely with data scientists, software engineers, and product managers, gaining exposure to the full development lifecycle. These experiences help build both technical and teamwork skills, laying a strong foundation for a future career in the field.

What is the difference between Internship Full Stack Machine Learning Engineer vs Software Developer Intern?

AspectInternship Full Stack Machine Learning EngineerSoftware Developer Intern
Required SkillsKnowledge of machine learning, programming (Python, JavaScript), full stack development, data handlingProficiency in programming languages (Java, Python, JavaScript), software development, basic algorithms
Work EnvironmentCollaborates on ML models, data pipelines, backend and frontend developmentFocuses on application development, coding, debugging, and testing
Industry UsageUsed in AI-driven companies, tech startups, data science teamsCommon in software firms, app development companies, tech startups

The Internship Full Stack Machine Learning Engineer role emphasizes working with machine learning models and data-driven applications, combining full stack development skills with AI expertise. In contrast, a Software Developer Intern focuses more on traditional software development tasks like coding and debugging. Both roles are valuable entry points in tech, but they target different skill sets and project types.

What are popular job titles related to Internship Full Stack Machine Learning Engineer jobs in Queens, NY? For Internship Full Stack Machine Learning Engineer jobs in Queens, NY, the most frequently searched job titles are:
What job categories do people searching Internship Full Stack Machine Learning Engineer jobs in Queens, NY look for? The top searched job categories for Internship Full Stack Machine Learning Engineer jobs in Queens, NY are:
What cities near Queens, NY are hiring for Internship Full Stack Machine Learning Engineer jobs? Cities near Queens, NY with the most Internship Full Stack Machine Learning Engineer job openings:
Internship Full Stack Machine Learning Engineer jobs near you

Machine Learning Engineer

Goodfire

Manhattan, NY • On-site

Full-time

Re-posted 3 days ago

Job description

Job Summary:
Goodfire is a research company focused on understanding and designing AI systems. They are seeking Machine Learning Engineers to build a platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to the development of core technology and product features.
Responsibilities:
• Turn cutting edge interpretability research into production ready tools.
• Optimize pipelines and infrastructure for frontier model interpretability, training, and inference.
• Integrate new machine learning workflows and pipelines into our product and deploy to customers.
• Ensure system reliability, reproducibility, and performance.
Qualifications:
Required:
• 5+ years of experience in ML infra, research engineering, or systems programming.
• Comfort working across research and engineering boundaries.
• Expertise in Python, PyTorch or Jax, and distributed systems.
• Experience deploying and maintaining ML systems at scale.
• You care about understanding how models work internally and using that to make them more reliable and useful in the real world.
Preferred:
• Open-source ML infra contributions.
• Startup or frontier lab experience in fast-moving teams.
Company:
Goodfire is an AI research lab using interpretability to turn AI into something that can be understood, debugged, and shaped like software Founded in 2024, the company is headquartered in San Francisco, USA, with a team of 11-50 employees. The company is currently Early Stage.

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