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Undergraduate Machine Learning Jobs (NOW HIRING)

Apple

Sr. Machine Learning Engineer - Finance

Austin, TX

$181K - $272K/yr

As a machine learning engineer in Finance, you'll play an integral and global role in building the ... Undergraduate degree (computer science, data science, finance, economics, accounting, or related ...

Vanguard

Manager, Machine Learning Engineer

Dallas, TX

$101K - $133K/yr

Leads a team of Machine Learning Engineers responsible for designing, building, deploying, and ... Undergraduate degree or equivalent combination of training and experience. Graduate degree ...

Apple

Sr. Machine Learning Engineer - Finance

Austin, TX

$181K - $272K/yr

As a machine learning engineer in Finance, you'll play an integral and global role in building the ... Undergraduate degree (computer science, data science, finance, economics, accounting, or related ...

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Undergraduate Machine Learning information

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How much do undergraduate machine learning jobs pay per hour?

As of Jul 3, 2026, the average hourly pay for undergraduate machine learning in the United States is $21.33, according to ZipRecruiter salary data. Most workers in this role earn between $18.75 and $22.84 per hour, depending on experience, location, and employer.

Which 3 jobs will survive AI?

For undergraduate machine learning students, roles such as data scientists, AI researchers, and machine learning engineers are expected to persist due to their reliance on complex problem-solving, domain expertise, and creativity. These jobs require advanced understanding of algorithms, programming skills, and critical thinking that are less easily automated. Continuous learning and specialization in tools like Python, TensorFlow, or cloud platforms will enhance job security in these fields.

What is the difference between Undergraduate Machine Learning vs Data Scientist?

AspectUndergraduate Machine LearningData Scientist
Required CredentialsBachelor's degree in CS, Data Science, or related fieldOften requires advanced degrees (Master's or PhD) in Data Science, Statistics, or related fields
Work EnvironmentAcademic projects, internships, entry-level roles in tech companiesData analysis, modeling, and insights generation in various industries
Industry UsageEducational programs, research, entry-level industry rolesBusiness, finance, healthcare, tech, and more

Undergraduate Machine Learning focuses on foundational knowledge and entry-level skills in machine learning algorithms and programming. Data Scientists build on this foundation, applying advanced analytics, statistical methods, and domain expertise to solve complex business problems. While both roles require a strong understanding of data and algorithms, Data Scientists typically have more experience and advanced education, working in diverse industries to generate insights and support decision-making.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer, AI research director, or executive role, often offering compensation including salary, bonuses, and stock options. These roles usually require advanced skills in machine learning, deep learning, and data science, along with significant experience and sometimes advanced degrees. Such positions are rare and generally found in leading tech companies or AI-focused organizations.

What are entry-level AI/ML jobs?

Entry-level AI/ML jobs typically include roles such as Machine Learning Engineer, Data Analyst, or AI Research Assistant. These positions often require foundational knowledge of programming languages like Python, familiarity with machine learning frameworks such as TensorFlow or PyTorch, and a relevant degree or certification. They offer opportunities to gain practical experience in developing and deploying AI models in a professional environment.

What engineer makes $500,000 a year?

Senior machine learning engineers and AI specialists with extensive experience, advanced skills in deep learning, and strong industry demand can earn $500,000 or more annually, especially in high-paying sectors like technology and finance. Achieving this level typically requires advanced degrees, certifications, and a track record of impactful projects.

What are the key skills and qualifications needed to thrive as an Undergraduate in Machine Learning, and why are they important?

To thrive as an undergraduate in machine learning, you need a strong grounding in mathematics (especially linear algebra, calculus, and statistics), programming skills (commonly in Python), and fundamental knowledge of algorithms and data structures. Familiarity with machine learning libraries like scikit-learn, TensorFlow, or PyTorch, as well as experience using data analysis tools such as Jupyter Notebooks, is highly valuable. Critical thinking, curiosity, and the ability to collaborate and communicate complex ideas effectively are standout soft skills in this field. These competencies are vital for successfully navigating coursework, conducting research, and solving real-world problems using machine learning methods.

What are undergraduate machine learning positions?

Undergraduate machine learning positions are entry-level roles, internships, or research opportunities designed for students pursuing a bachelor's degree who have an interest in machine learning. These positions typically involve assisting with data analysis, model development, and research projects under the supervision of experienced professionals or academics. They provide hands-on experience with machine learning algorithms, programming, and data processing, helping students build practical skills for future careers or graduate study in the field.

How do undergraduate machine learning roles typically balance independent work with team collaboration?

In undergraduate machine learning roles, you can expect a mix of independent research or coding tasks and collaborative projects with peers or supervisors. While you may spend significant time developing models or analyzing datasets on your own, regular meetings, code reviews, and brainstorming sessions with team members are common. This collaboration not only helps you refine your technical skills but also exposes you to different problem-solving approaches and feedback. Working closely with others is also a great opportunity to build your professional network and gain insights into real-world applications of machine learning.
More about Undergraduate Machine Learning jobs
What are the most commonly searched types of Undergraduate Machine Learning jobs? The most popular types of Undergraduate Machine Learning jobs are:
What job categories do people searching Undergraduate Machine Learning jobs look for? The top searched job categories for Undergraduate Machine Learning jobs are:
Undergraduate Machine Learning jobs near you
Infographic showing various Undergraduate Machine Learning job openings in the United States as of June 2026, with employment types broken down into 10% Internship, 80% Full Time, 5% Part Time, and 5% Contract. Highlights an 95% In-person, and 5% Remote job distribution, with an average salary of $44,363 per year, or $21.3 per hour.
Director, Machine Learning, Virtual Cell Initiative

Director, Machine Learning, Virtual Cell Initiative

Arc Institute

Palo Alto, CA • On-site

Full-time

Posted 6 days ago

Job description

Job Summary:
Arc Institute is an independent nonprofit research organization at the intersection of artificial intelligence and biology, aiming to accelerate scientific progress. They are seeking a Director for the Machine Learning Virtual Cell Initiative to lead the development of predictive models based on single-cell genomic data and collaborate with a multidisciplinary team.
Responsibilities:
• Lead/build a team of 6 ML research scientists and engineers augmented with undergrad/masters/PhD students to contribute to the development of a state-of-the-art foundation model and agentic framework for understanding how cells respond to perturbations.
• Work in an active learning loop with Arc’s wet lab scientists to shape the world's largest and most diverse set of single cell training data across many cell contexts.
• Collaborate closely with other research groups to integrate genomics, functional track, and omics data more broadly beyond scRNA-seq data and Perturb-seq.
• Stay up to date on the latest in frontier ML research and pioneer new architectures and approaches.
• The ultimate goal is to build a high utility virtual cell model for use by biologists worldwide. We publish our breakthroughs to widely accelerate scientific progress and partner with some of the biggest names in AI.
• Commit to a collaborative and inclusive team environment, sharing expertise and mentoring others.
• Attract the very best talent in the world to support VCI initiative goals.
Qualifications:
Required:
• PhD in Computational Biology, Bioinformatics, Machine Learning, or a related field.
• Minimum of 5 years of experience working in/with machine learning, well versed in frameworks such as Pytorch, TensorFlow, JAX, etc.
• Proven experience leading research teams in a fast paced, multi-disciplinary environment.
• Experience with or strong interest in biology with ability to communicate and collaborate successfully with biologists and pure ML engineers.
• Excellent communication skills, both written and verbal, with a strong track record of presentations and publications.
Company:
Arc Institute is a biomedical science and research technology company. Founded in 2021, the company is headquartered in Palo Alto, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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