AI/ML Engineers

AI/ML Engineers design, develop, and deploy machine learning models and artificial intelligence systems. They work at the intersection of software engineering and data science, building the algorithms and infrastructure that power intelligent applications from recommendation systems to autonomous vehicles. These professionals work across nearly every industry, with particularly high demand in technology, finance, healthcare, and e-commerce. Most work in office or hybrid settings at tech companies, startups, research labs, or as part of digital transformation teams at traditional enterprises. The work involves significant coding, experimentation, and collaboration with data scientists and product teams. This career offers exceptional compensation, strong job security, and the opportunity to work on cutting-edge technology that shapes the future. AI/ML Engineers often advance to Staff/Principal roles, move into AI research, or transition to technical leadership positions. The field requires continuous learning as techniques evolve rapidly.

Median Annual Pay

$175,000

Range: $115,000 - $300,000

Training Time

4-7 years

AI Resilience

🟡AI-Augmented

Education

Bachelor's degree

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🤖AI Resilience Assessment

AI Resilience Score

AI/ML Engineers have moderate exposure to AI automation because while AI tools can assist with code generation, data preprocessing, and model prototyping, the core work of designing novel architectures, understanding domain problems, and making strategic technical decisions requires deep human judgment. The field is experiencing 35%+ growth driven by AI adoption across industries. Human advantages include high creativity in developing new approaches and strong judgment in balancing model performance, interpretability, and ethical considerations. AI tools augment rather than replace these professionals.

🟡AI-Augmented

How we calculated this:

AI Exposure

Medium+1

35% of tasks can be accelerated by AI

Job Growth

Rapid Growth+2

+35% projected (2024-2034)

Human Advantage

Moderate+1

EPOCH score: 15/25

Total Score4/6

Methodology: v2.0 - GPTs are GPTs / BLS / EPOCH Additive ScoringUpdated: 2026-01-08

View full methodology →

📋Key Responsibilities

•Design and implement machine learning models for specific business problems
•Train, evaluate, and optimize models for performance and efficiency
•Build and maintain ML pipelines for data processing and model deployment
•Collaborate with data scientists and product teams to translate requirements into ML solutions
•Deploy and monitor models in production environments
•Research and evaluate new ML techniques and frameworks
•Optimize inference performance and reduce computational costs
•Ensure models meet fairness, privacy, and security requirements

📈Career Progression

What does this mean?

This shows how earnings typically grow with experience. Entry level represents starting salaries, while Expert shows top earners (90th percentile). Most workers reach mid-career earnings within 5-10 years. Figures are national averages and vary by location and employer.

Entry (10th %ile)

0-2 years experience

$115,000

$103,500 - $126,500

Early Career (25th %ile)

2-6 years experience

$140,000

$126,000 - $154,000

Mid-Career (Median)

5-15 years experience

$175,000

$157,500 - $192,500