How to compare a nearshore engineer to a US hire using only public BLS data
US hiring teams often compare a nearshore rate with a US salary and stop there. That comparison is incomplete: a salaried employee also costs benefits, paid leave and the employer's payroll taxes. The US government publi
US hiring teams often compare a nearshore rate with a US salary and stop there. That comparison is incomplete: a salaried employee also costs benefits, paid leave and the employer's payroll taxes. The US government publishes those pieces. You can rebuild a fully loaded US cost from them, then compare it with an all-in hourly rate, without relying on a vendor's private spreadsheet.
This walk-through uses only official Bureau of Labor Statistics (BLS) releases, plus a worked example with the all-in ranges Bromena publishes for AI and data roles. Every arithmetic step is below, so you can swap in your own salary or rate and rerun it.
1. Start with a US wage that actually has a BLS category
BLS does not publish a national wage series named "machine learning engineer" or "data engineer". The closest occupation with national data is software developers.
From the Occupational Outlook Handbook, pay for May 2025:
- Median annual wage: $135,980
- Highest 10 percent (the 90th percentile): more than $214,670
Source: BLS, Occupational Outlook Handbook, Software Developers.
If your team pays above those figures, the gap you calculate later will be wider. If you have a wage for the exact role you are filling, use that instead of the national median.
2. Turn the wage into a fully loaded employer cost
Wages are not what a US employer spends. The BLS Employer Costs for Employee Compensation (ECEC) series splits private-industry compensation into wages and benefits.
In June 2026, for private industry workers:
- Total compensation averaged $46.89 per hour worked
- Wages and salaries averaged $32.82, or 70.0 percent of that total
- Benefit costs averaged $14.07, or the remaining 30.0 percent
The release date is 9 September 2026 (USDL-26-1494). Source: BLS, Employer Costs for Employee Compensation, June 2026.
Dividing a wage by 0.70 adds the benefits layer:
- Median: $135,980 / 0.70 = $194,257
- 90th percentile: $214,670 / 0.70 = $306,671
Two caveats, both of which shrink the US figure relative to a real hire:
- ECEC's 70.0 percent is an average across private industry, not a software-only ratio. It is the official number you can cite without mixing surveys.
- This still leaves out recruiting fees and the months a role stays empty. Those costs are real, but they have no single public series that belongs in the same table, so they stay out of the comparison.
3. Price the same year with an all-in hourly rate
An all-in nearshore rate already includes the engineer's pay and the vendor's fee. To put it on an annual basis, multiply by 2,080 hours, the full-time year BLS uses for annual wages.
Worked example, using ranges Bromena reviewed in October 2026 for AI and data roles (the low end of each range is mid-level; the high end is lead):
| Comparison | US hire, fully loaded | Nearshore, 2,080 hours | Difference |
|---|---|---|---|
| Roles other than data engineer, low end ($65/hour) | $194,257 | $135,200 | 30% less |
| Same roles, high end ($105/hour) | $306,671 | $218,400 | 29% less |
| Data engineer, low end ($58/hour) | $194,257 | $120,640 | 38% less |
| Data engineer, high end ($88/hour) | $306,671 | $183,040 | 40% less |
The arithmetic, so you can check it:
- $65 Γ 2,080 = $135,200; ($194,257 β $135,200) / $194,257 β 30%
- $105 Γ 2,080 = $218,400; ($306,671 β $218,400) / $306,671 β 29%
- $58 Γ 2,080 = $120,640; ($194,257 β $120,640) / $194,257 β 38%
- $88 Γ 2,080 = $183,040; ($306,671 β $183,040) / $306,671 β 40%
Cloud, GPUs and model API usage are not in either column. They should run on the customer's accounts in both models.
4. What this does not claim
- It does not say every nearshore engineer costs 29 to 40 percent less. That range is the result of this method, with these inputs, for these published rates.
- It does not treat "software developers" as the same job as an ML or data engineer. It treats it as the closest official wage category, and says so.
- It does not include output, seniority mix, or the cost of a bad hire. Those belong in a hiring decision, not in this table.
If you want to rerun the same steps with a different US wage or a quoted rate, Bromena publishes a calculator that follows this method and lists the same sources.
Sources
- U.S. Bureau of Labor Statistics, Occupational Outlook Handbook, Software Developers, pay for May 2025: https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm
- U.S. Bureau of Labor Statistics, Employer Costs for Employee Compensation, June 2026, released 9 September 2026 (USDL-26-1494): https://www.bls.gov/news.release/ecec.nr0.htm
β Bromena team
Originally published by Dev.to AI. Aggregated on AIWithGhost for educational purposes β full credit and traffic to the original publisher.