Housing
Housing dominates Celina's monthly budget at $1,174, with a 1-bedroom city center apartment averaging $917. Basic utilities add $188 monthly for an 85m2 apartment, while internet runs $58 for high-speed service.
Market ranges & how to evaluate your offer
Most offers in Celina fall between $213k–$405k depending on seniority, location, and role scope.
Local vs National
Celina
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 Celina, TX market.
Estimated monthly costs for this basket are about 61% 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.
$1,483.86/ mo
HOUSING
$1,174.11 USD (79.1% of est. monthly costs)
FOOD
$167.20 USD (11.3% of est. monthly costs)
TRANSPORT
$41.50 USD (2.8% of est. monthly costs)
LIFESTYLE
$101.05 USD (6.8% of est. monthly costs)
Housing dominates Celina's monthly budget at $1,174, with a 1-bedroom city center apartment averaging $917. Basic utilities add $188 monthly for an 85m2 apartment, while internet runs $58 for high-speed service.
Food costs remain modest at $167 monthly in this Texas suburb. Basic groceries show reasonable pricing with chicken at $10/kg and eggs at $3 per dozen, while restaurant meals average $12 for inexpensive dining options.
Public transit costs just $42 monthly for a regular pass. Given Celina's suburban Dallas location, many tech professionals likely drive to nearby employment hubs in Plano or Dallas proper for work commutes.
Discretionary spending totals $101 monthly with gym memberships at $39 and movie tickets at $12. Coffee runs about $4 per cappuccino, keeping entertainment costs reasonable compared to the housing-heavy budget structure.
Salary data only matters if you land the interview. Get a free AI-powered resume review and see how yours stacks up.
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.
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