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Machine Learning / AI

Design and train models that power recommendation systems, language models, and autonomous systems at top tech companies.

$120K$250K / yrTechResearchHigh GrowthProgramming

Overview

Machine learning engineers and AI researchers apply linear algebra, probability, optimization, and calculus to build systems that learn from data. The mathematical foundations are central — understanding gradient descent, eigendecompositions, kernel methods, and information theory separates strong practitioners from average ones. Math majors are highly sought after for research roles at AI labs and ML-heavy tech companies.

A Day in the Life

9:00 AM
analysis

Review training runs from overnight experiments

10:00 AM
meeting

Research meeting on attention mechanism improvements

11:00 AM
study

Derive gradient update rules for custom loss function

1:30 PM
work

Implement and test new architecture in PyTorch

3:30 PM
analysis

Evaluate model performance against benchmarks

5:00 PM
work

Write internal research report on findings

Growth Outlook

Very strong — BLS projects computer and information research scientist employment to grow 20% from 2024 to 2034, much faster than average.

Source: BLS 2024-34 projection

Recommended Courses

Linear Algebra
Real Analysis
Probability Theory
Numerical Optimization
Functional Analysis
Statistics

Required Skills

Linear AlgebraMultivariable CalculusProbability & StatisticsPythonOptimization TheoryInformation Theory

Top Employers

  • Google DeepMind
  • OpenAI
  • Meta AI
  • Apple
  • NVIDIA
  • Anthropic

Salary Range

$120K$250K

per year, US market

Source: BLS computer and information research scientists