Market ranges & how to evaluate your offer
Most offers in Apex fall between $213k–$405k depending on seniority, location, and role scope.
Local vs National
Apex
Salary data is self-reported and varies by scope, company, and location. Use ranges, not single numbers.
Compare your total comp for Machine Learning Engineer — pick seniority, enter an offer, and preview the layout. Percentiles use your selected seniority when market data is available.
Seniority-level breakdown for this market.
Cost of living breakdown for Apex, NC market.
Estimated monthly costs for this basket are about 90% of our comparable national baseline—day-to-day spending tends to go further here.
How the estimated monthly cost bundle splits across categories for a typical Machine Learning Engineer earner.
$2,197.07/ mo
HOUSING
$1,871.71 USD (85.2% of est. monthly costs)
FOOD
$196.26 USD (8.9% of est. monthly costs)
TRANSPORT
$20.00 USD (0.9% of est. monthly costs)
LIFESTYLE
$109.10 USD (5.0% of est. monthly costs)
Housing dominates the budget at $1,872 monthly, with downtown one-bedroom apartments averaging $1,611. Utilities add $170 for basics like electricity and water, while high-speed internet runs $64. This suburban Raleigh metro location reflects typical housing costs for professionals seeking proximity to Research Triangle employment centers.
Food expenses total $196 monthly, with grocery staples reasonably priced—milk at $0.93 per liter and chicken fillets at $9.32 per kg. Restaurant meals average $15 for inexpensive dining. These costs align with moderate suburban pricing, offering good value compared to major metropolitan areas while supporting the area's growing professional population.
Public transit costs just $20 monthly for a regular pass, reflecting limited but affordable options in this suburban setting. Most professionals likely rely on personal vehicles for commuting to nearby Raleigh, Cary, or Research Triangle Park employment hubs, given Apex's car-oriented infrastructure and regional job distribution patterns.
Discretionary spending totals $109 monthly, with gym memberships at $36 and movie tickets at $12 representing solid suburban values. Coffee runs about $5 for cappuccinos at local establishments. These moderate lifestyle costs support a comfortable standard of living while keeping discretionary expenses well below housing commitments.
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Location-specific ranges with optional cost-of-living adjustment.
Machine Learning Engineer remote compensation varies significantly based on company pay philosophy and location adjustments. Tech giants like Google and Meta typically offer location-adjusted salaries, paying SF/NYC rates around $180-250K base while adjusting Austin or Denver roles to $150-200K base. However, many AI startups and remote-first companies like Hugging Face or Weights & Biases offer national pay bands, providing equal compensation regardless of location to attract top ML talent.
The hybrid work trend has created tiered compensation structures for Machine Learning Engineers, with many companies offering 90-100% of office pay for hybrid roles and 80-95% for fully remote positions. When negotiating, emphasize your ability to collaborate on distributed ML teams and experience with remote model development workflows. Companies value ML engineers who can effectively communicate complex technical concepts across time zones and manage distributed training experiments.
Moving from high-cost metros like San Francisco ($200K+ typical) to lower-cost areas while maintaining remote ML work can dramatically improve purchasing power. A $180K remote ML engineer salary in Austin or Raleigh provides equivalent lifestyle to $250K+ in the Bay Area, while cities like Denver or Nashville offer strong tech communities with 30-40% lower living costs than coastal hubs.
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How adjacent roles compare in pay and scope.
$120k-$495k
High overlap in software-engineer roles
Details$112k-$432k
High overlap in software-engineer roles
Details$117k-$402k
High overlap in software-engineer roles
Details$102k-$316k
High overlap in software-engineer roles
Details$123k-$420k
High overlap in software-engineer roles
Details$105k-$420k
High overlap in software-engineer roles
DetailsPractical steps that move the number without damaging the relationship.
Start your ask above the median. You'll rarely be offered more than you ask, so anchor high and let the employer negotiate you down.
Stronger approach:
Say 'market data puts this role at $X–$Y' — not 'I was hoping for more'. External benchmarks are harder to argue against than personal expectations.
Stronger approach:
When base is stuck, negotiate equity vesting schedule, signing bonus, or accelerated refresh grants. Total comp has more levers than base alone.
Stronger approach:
Ask for 48 hours to review. This creates time to counter and signals that you take offers seriously — not that you are uncertain.
Stronger approach:
Generate an aware negotiation email using Google market positioning data.
Mock interviews tailored to Google's process and evaluation criteria.
Common questions about Machine Learning Engineer compensation.
Tools built for professionals evaluating offers and preparing for interviews.
Our AI Interview Copilot listens to your live interview and feeds you real-time answers, so you walk in confident and walk out with the offer.
"I used the salary data to benchmark my offer, then generated a negotiation email. Got a 12% bump without a single awkward conversation."
