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New Grad Machine Learning information

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$25.5K

$42.6K

$88K

How much do new grad machine learning jobs pay per year?

As of Aug 22, 2026, the average yearly pay for new grad machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is a new grad machine learning?

New Grad Machine Learning roles are entry-level positions designed for recent graduates who have studied machine learning, artificial intelligence, data science, or related fields. These positions typically involve working with experienced data scientists and engineers to develop, implement, and improve machine learning models and algorithms. New grads in these roles often contribute to projects involving data preprocessing, model training, evaluation, and deployment. The goal is to help new graduates gain hands-on experience and grow their skills in a real-world setting while contributing to the organization's AI initiatives.

What skills and qualifications are needed to thrive as a new grad machine learning?

To thrive as a New Grad Machine Learning Engineer, you need a solid foundation in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch, version control systems like Git, and coursework or certification in data science are highly beneficial. Strong problem-solving abilities, curiosity, and effective communication skills help you collaborate and convey complex technical concepts to diverse teams. These skills and qualities are essential for developing innovative models, ensuring project success, and integrating seamlessly into fast-paced tech environments.

What challenges do new graduates face when starting out in a machine learning role, and how can they overcome them?

New grad machine learning engineers often encounter challenges such as bridging the gap between academic knowledge and practical, production-level projects. Adapting to real-world data issues, collaborating with cross-functional teams, and understanding scalable deployment can be daunting at first. To overcome these, it's helpful to seek mentorship, proactively ask questions, and dedicate time to learning best practices in code versioning, model evaluation, and team communication. Engaging in code reviews and participating in team discussions can also accelerate the learning curve and foster professional growth.

What is the difference between New Grad Machine Learning vs Data Scientist?

AspectNew Grad Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some internshipsBachelor's or Master's in CS, Statistics, or related; some experience
Work EnvironmentEntry-level, team-focused, research and developmentData analysis, modeling, cross-functional collaboration
Employer & Industry UsageTech companies, startups, research labsTech, finance, healthcare, consulting firms

New Grad Machine Learning roles typically focus on foundational skills, internships, and entry-level tasks, while Data Scientist positions often require more experience in data analysis and statistical modeling. Both roles are common in tech industries, but Data Scientists usually handle broader data analysis responsibilities.

More about New Grad Machine Learning jobs

What cities are hiring for New Grad Machine Learning jobs?

Cities with the most New Grad Machine Learning job openings:

What states have the most New Grad Machine Learning jobs?

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What job categories do people searching New Grad Machine Learning jobs look for?

The top searched job categories for New Grad Machine Learning jobs are:

New Grad Machine Learning jobs near you
Infographic showing various New Grad Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Engineer, Generative ML

Jobtailor

California, MO • On-site

$180 - $240/hr

Other

Posted 17 days ago

Job description

Responsibilities
  • Develop innovative machine learning technology and products that serve millions of Snapchatters
  • Work on state of the art GenAI pipelines for image, video, and audio generation
  • Deliver generative machine learning experiences on device
  • Build cutting-edge augmented reality experiences using generative and diffusion models
  • Partner with cross-functional Snap teams to explore and prototype new products
Requirements
  • Bachelor’s Degree in a technical field such as computer science, mathematics, statistics or equivalent years of experience
  • 5+ years of post-Bachelor’s machine learning experience; or Master's degree in a technical field + 4+ year of post-grad machine learning experience; or PhD in a relevant technical field + 1 years of post-grad machine learning experience
  • Research or engineering experience in one or more of the following: generative models, efficient models, segmentation, object detection, classification, tracking, or other related applications of machine learning
  • Strong software development skills in Python or C++
  • Proficiency working with major deep learning frameworks: PyTorch or TensorFlow
  • Knowledge of mathematics and deep learning foundations
  • Desire to solve open ambiguous problems
  • Desire to grow professionally, learn and help others
  • Ability to effectively collaborate with internal teams and external partners
  • Ability to work independently
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