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Math Degree Machine Learning Jobs (NOW HIRING)

Samprasoft

Machine Learning Engineer

Mclean, VA · On-site

At least a Bachelor's degree in Computer Science, Mathematics, related technical field or equivalent practical experience. * A blend of data engineering, machine learning, and product innovation ...

SysMind Tech

Machine Learning

Manhattan, NY · On-site

$85/hr

Title - Machine Learning ( F2F interview is required) Location - New York, NY ( Hybrid 2-3 days ... s degree in Computer Science, Statistics, Applied Mathematics, or a related field. Minimum of 2 ...

ManTech

Machine Learning Engineer

Herndon, VA

Master's degree in Applied Mathematics, Statistics, Computer Science, or related fields. * Verifiable work experience defining and implementing data pipelines and machine learning algorithms.

Stefanini

Machine Learning Engineer

Allen Park, MI

... Learning (ML), predictive modeling, math, statistics, advanced analytics, etc. Key ... Degree Education PreferredCertification Program **Listed salary ranges may vary based on experience ...

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Math Degree Machine Learning information

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$58.8K

$94.5K

How much do math degree machine learning jobs pay per year?

As of Jun 20, 2026, the average yearly pay for math degree machine learning in the United States is $58,837.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,000.00 and $70,000.00 per year, depending on experience, location, and employer.

Is math a good major for machine learning?

A math degree is highly valuable for machine learning roles like data scientist or machine learning engineer, as it provides a strong foundation in algorithms, statistics, and linear algebra essential for developing models. Proficiency in programming languages such as Python and familiarity with machine learning frameworks are also important for success in this field.

What can you do with a math degree in machine learning?

A math degree provides a strong foundation for a career in machine learning, as the field relies heavily on mathematical concepts such as statistics, linear algebra, and calculus. With a math degree, you can pursue roles like data scientist, machine learning engineer, quantitative analyst, or research scientist. Your mathematical background will help you design algorithms, analyze large datasets, and develop predictive models that drive advancements in technology and industry.

How does having a math degree enhance your effectiveness in a machine learning role?

A math degree provides a strong foundation in areas such as linear algebra, calculus, probability, and statistics, which are crucial for understanding and developing machine learning algorithms. This background enables you to grasp the theoretical underpinnings of models, optimize algorithms, and troubleshoot issues that arise in real-world applications. In a machine learning team, this expertise often positions you to tackle complex modeling challenges, collaborate closely with data scientists and engineers, and contribute to research or innovation within the organization.

Which 3 jobs will survive AI?

For a math degree with machine learning skills, roles such as data scientist, machine learning engineer, and AI researcher are likely to persist as they require complex problem-solving, domain expertise, and ongoing innovation that are difficult for AI to fully automate. These jobs involve designing, developing, and interpreting advanced algorithms, often requiring strong mathematical and programming skills. Continuous learning and staying updated with new tools like Python, TensorFlow, or PyTorch are essential for long-term career resilience.

What are the key skills and qualifications needed to thrive in a machine learning role with a math degree, and why are they important?

To thrive in a machine learning role with a math degree, you need a strong background in mathematics (such as linear algebra, probability, and statistics), programming skills (often in Python or R), and knowledge of machine learning concepts. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and proficiency in using data analysis and visualization platforms are typically expected. Excellent problem-solving abilities, critical thinking, and clear communication help you interpret data, collaborate with teams, and present findings effectively. These skills and qualities are crucial for building robust machine learning models, driving data-driven decisions, and contributing to organizational innovation.

Does Nvidia hire math majors?

Nvidia hires math majors for roles in machine learning, data science, and AI research, often requiring strong mathematical skills, programming experience, and knowledge of tools like Python and TensorFlow. Candidates with a background in mathematics and relevant technical skills are well-suited for positions in Nvidia's AI and deep learning teams.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles such as senior machine learning engineers, AI research directors, or data science executives, often in large tech companies or finance firms. These positions usually require advanced skills in machine learning, deep learning, and programming, along with extensive experience and sometimes advanced degrees. Compensation at this level includes base salary, bonuses, and stock options, reflecting the role's seniority and impact.

What is the difference between Math Degree Machine Learning vs Data Scientist?

AspectMath Degree Machine LearningData Scientist
Required CredentialsMath degree, programming skills, knowledge of ML algorithmsStatistics, programming, domain expertise, often a math or CS background
Work EnvironmentResearch labs, tech companies, startups, academiaBusiness settings, tech firms, consulting, finance
Employer & Industry UsageTech companies, research institutions, AI startupsVarious industries including finance, healthcare, marketing
Search & Comparison IntentFocus on technical ML skills, algorithms, modelingData analysis, insights, business impact

Math Degree Machine Learning professionals specialize in developing and applying machine learning models using advanced math and programming skills. Data Scientists analyze data to extract insights and support decision-making, often utilizing statistical and analytical techniques. While both roles require strong technical backgrounds, Math Degree Machine Learning roles are more focused on algorithm development, whereas Data Scientists emphasize data analysis and business applications.

Machine Learning Engineer

Machine Learning Engineer

Radiance Technologies

Beavercreek, OH • On-site

Other

Medical, Dental, Vision, Life, Retirement

Posted 9 days ago

Job description

Radiance is seeking a Machine Learning Engineer who will advance the artificial intelligence capabilities of the National Air and Space Intelligence Center at Wright Patterson Air Force Base. This engineer will provide expertise in data analytics and algorithm development supporting the integration and analysis of diverse data sources and develop machine learning, data mining and statistical algorithms for pattern recognition and anomaly detection. Additionally, this position will improve upon current methods for the automated processing and exploitation of large data sets. This will include R&D on projects involving the exploitation of data from sensors including investigation of state-of-the-art machine learning classification methods to detect, track, and characterize targets of interest.
Radiance Technologies is an employee-owned company with benefits that are unmatched by most companies in the Dayton OH area. Employee ownership, generous 401K, full health/dental/life/vision insurance benefits, interesting assignments, educational reimbursement, competitive salaries and a pleasant work environment combine to make Radiance Technologies a great place to work and succeed.
Required Experience:

  • A working knowledge of Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs)
  • Experience in applying core Machine Learning methodologies: Regression, Classification, Clustering, Decision Trees, Dimensional Reduction, Neural Networks & Deep Learning, Feature Engineering
Required Skills & Qualifications:
  • Bachelor's Degree in a quantitative field such as Physics, Engineering, Computer Science, Statistics, or a related field
  • Strong programming skills in at least one of the following languages Python, Matlab, C++
  • Experience with Machine Learning APIs, such as TensorFlow, PyTorch, or Keras
  • Active Secret Clearance with ability to obtain and maintain a TS/SCI
Desired Skills:
  • ML for either natural language processing, computer vision, reinforcement learning, generative modeling, or equivalent experience
  • PhD in data science, mathematics, statistics, computer science, a physical science or engineering is strongly desired
  • A mathematical background (Probability and Statistics)
  • An experienced grasp of version control using Git for nonlinear workflows
  • Thorough understanding of working in research, development and production environments
  • Background in image science, imagery exploitation, spatial analysis, and computer vision are a plus
  • R&D on remotely sensed data to include modeling and development of algorithms.
  • Ability to work independently or in a team environment
  • Strong technical writing and oral communication skills
  • Active Top Secret/SCI clearance

Radiance Technologies is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.

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