Machine Learning Engineer Salary in Houston — 2026 BLS Data

$132K median base salary · Houston

BLS OEWS · 2024 data

Salary distribution

Percentile breakdown of Machine Learning Engineer base salaries in Houston.

25th percentile

$102K

50th (median)

$132K

75th percentile

$163K

90th percentile

$196K

The BLS OEWS May 2024 release puts the Houston-Pasadena-The Woodlands metro median for Data Scientists (SOC 15-2051 — the federal classification that covers most machine learning engineering work) at $100,420. Machine Learning Engineers in practice command a consistent premium over generalist data scientists because they combine statistical modeling depth with production engineering: training pipelines, serving infrastructure, latency budgets, and model monitoring. Triangulating the BLS Houston DS baseline with current salary databases, that premium runs 25–32% in the Houston market, landing the MLE P50 at approximately $132,000 in base salary. That figure tracks closely with multiple market sources, including Indeed’s reported average of $142,553 and Built In’s average of $132,000 for Houston MLEs. What the median hides is more consequential than the number itself.

Houston machine learning engineer salary percentiles (BLS OEWS May 2024)

The percentile figures below are derived from BLS OEWS May 2024 data for SOC 15-2051 in the Houston-Pasadena-The Woodlands MSA — sourced via O*NET regional wage tool and BLS OEWS metro tables — adjusted for the market-documented MLE premium over the Data Scientist baseline. The BLS DS percentile anchors for this metro are P25 $80,250, P50 $100,420, P75 $132,380, P90 $164,300. The resulting MLE estimates:

Percentile	Annual Base Salary
P25	$102,000
P50 (Median)	$132,000
P75	$163,000
P90	$196,000

The $94,000 range between P25 and P90 reflects a genuinely fragmented market. “Machine Learning Engineer” at a regional hospital system and “Machine Learning Engineer” at ExxonMobil’s advanced AI division are the same job title on a resume and entirely different jobs in practice — different scope, different infrastructure complexity, different pay. The BLS bucket captures both.

What the median doesn’t tell you

The $132,000 median is a snapshot of a broad population: engineers at every experience level, every industry, and every definition of the word “production.” It obscures at least four distinct labor market segments in Houston that behave quite differently from each other.

At P25 ($102,000), you’re looking at roles that involve some modeling work — perhaps training a demand forecasting model or building a classification pipeline — but without the deployment and infrastructure ownership that defines genuine MLE scope. These are often titled “Data Scientist” or “ML Engineer” interchangeably, at smaller energy services companies, regional healthcare systems, or early-stage firms using ML to augment a primarily analytical function. Houston’s Texas Medical Center anchors a significant number of P25-range roles: Houston Methodist and academic medical center pay for clinical data science runs $53,000–$101,000 per Levels.fyi data, well below the commercial market.

At P75 ($163,000), you’re in the range of senior MLEs at energy majors or mid-level engineers at the handful of tech-forward employers in Houston — roles that own the full lifecycle from feature engineering through production deployment and model monitoring. By this level, the engineer has shipped multiple models at scale and has a clear track record of business impact.

At P90 ($196,000), the population includes staff-level engineers defining ML architecture across org boundaries, senior MLEs at energy supermajors with specialized domain knowledge (reservoir simulation, predictive maintenance at production scale, supply chain optimization), and engineers at the rare software-first company with a Houston presence. This tier also captures some remote-first engineers living in Houston and working for Bay Area or NYC employers at coastal pay bands — a segment growing in visibility since 2021.

The transition from P50 to P75 in this market is more about what you build and where you build it than years of experience alone. An engineer four years into their career who owns a production inference pipeline at a major energy company is comfortably at P75. An engineer with seven years of experience doing batch prediction at a healthcare analytics vendor may still sit near P50.

Houston vs. other machine learning hubs

Houston ranks behind Austin, Dallas, Seattle, New York, and San Francisco on raw MLE base salary. The gap at the national level is real: BLS OEWS May 2024 puts the national median for SOC 15-2051 at $112,590, but the MLE premium and metro-level competition push national MLE P50s higher. For comparison:

Market	Estimated MLE Median Base	COL Index
San Francisco	~$215,000	~178
Seattle	~$190,000	~142
New York City	~$180,000	~168
Austin, TX	~$155,000	~119
Dallas-Fort Worth	~$130,000	106
National Median (DS SOC)	~$112,590	100
Houston	~$132,000	94
Chicago	~$112,000	107

Houston’s raw number sitting above the national DS median but below Austin and Dallas reflects a market shaped by dominant energy and healthcare employers rather than software-first companies. The energy sector pays well, but the ML work there is more specialized and the employer set is narrower than in tech-dense markets. Companies like ExxonMobil, Shell, bp, and Chevron have invested significantly in AI and ML, and their senior ML pay is genuinely competitive — but the volume of roles is smaller than in a software-dense market.

The COL correction closes much of the gap. Houston’s cost-of-living index of 94 means living costs run approximately 6 percent below the US average — and roughly 47 percent below San Francisco. A $132,000 Houston MLE salary carries the purchasing power of approximately $140,000 at the national baseline, or $219,000 in San Francisco equivalent terms on a straight COL adjustment. Houston has no state income tax — the same Texas advantage Dallas and Austin cite — which is worth another 5–9% of gross income versus California at high income levels.

On a COL-adjusted basis, Houston’s MLE market looks significantly more competitive than raw salary figures suggest. Against Dallas ($130K median, COL 106), Houston ($132K median, COL 94) actually has slightly stronger real purchasing power.

What drives the spread: company tier, level, and ML specialty

Three factors account for most of the P25-to-P90 distance in Houston’s MLE market.

Company tier

The employer is the single largest variable in Houston MLE compensation.

Energy supermajors. ExxonMobil, Shell, bp, Chevron, and ConocoPhillips have built substantial ML teams in Houston to work on predictive maintenance, drilling optimization, refinery throughput modeling, supply chain forecasting, and — increasingly — LLM-based contract and regulatory document intelligence. ExxonMobil’s data science and ML engineering roles in the Houston area show total compensation reaching $180,000–$250,000+ for senior and staff levels per Levels.fyi data, with base salary forming the majority of comp. This tier pays base-heavy, offers real annual bonus programs (10–20% of base), and substitutes defined-benefit pension and ESPP for the equity structures common at software companies. For production MLEs with domain knowledge in industrial processes, this employer tier anchors the P75–P90 range in the Houston market.

Large oilfield services and midstream companies. Halliburton, Baker Hughes, SLB, and pipeline operators have active ML and AI teams focused on seismic interpretation, subsurface modeling, predictive maintenance, and field operations optimization. Compensation runs $110,000–$160,000 base for mid-level MLEs, with bonus programs that are meaningful but smaller than the supermajors’. This tier covers a large share of the P50–P75 range.

Healthcare and medical center. The Texas Medical Center is the world’s largest medical complex — 62 institutions, 106,000 daily visitors, more than 100,000 employees — and it generates steady ML demand in clinical decision support, imaging AI, genomics pipelines, and operations optimization. MD Anderson, Houston Methodist, UTHealth, and Memorial Hermann all hire MLEs, but the pay structure reflects academic and non-profit constraints. Base compensation typically runs $95,000–$130,000 for mid-level roles, with limited bonus and minimal equity. These roles sit at P40–P55 in the distribution.

Financial services and industrial tech. Hewlett Packard Enterprise, Sysco, Aramco Americas, and smaller fintech and insurtech companies fill out the mid-market. Compensation varies significantly — from $115,000 to $155,000 for mid-level — with equity programs that depend on whether the employer is publicly traded and how actively it competes for ML talent.

Remote-first at coastal pay bands. A growing segment: engineers living in Houston working for Bay Area, NYC, or Seattle employers who benchmark to national or regional pay bands. These roles land at $170,000–$220,000+ base for senior MLEs and sit above the BLS P90 anchor because the employer’s comp structure is derived from a higher-cost labor market. BLS metro data doesn’t capture remote-employer economics well, which partly explains why the P90 anchor ($196,000) understates what some Houston-area MLEs earn.

Level

BLS OEWS buckets all experience levels into one number. A rough level map for the Houston MLE market:

Entry-level (0–2 years): $85,000–$108,000. Model training support, feature engineering, some MLOps tasks under supervision. Primarily at energy services, healthcare analytics, or mid-size industrial companies.
Mid-level (3–5 years): $115,000–$152,000. Owns full model lifecycle end-to-end. Likely at an energy major, oilfield services company, or healthcare system.
Senior (6–9 years): $155,000–$185,000. System design decisions, cross-team influence, capable of mentoring junior engineers. At energy supermajors or senior-level roles at healthcare/industrial.
Staff/Principal (10+ years): $185,000–$230,000+. Defines ML architecture, shapes strategy across multiple product or engineering teams. Rare in Houston but present at supermajors and HPE.

Specialty and skill premium

Houston’s ML demand is heavily shaped by the industries present, and the market pays premiums for specialties those industries need.

Domain-specific model expertise — subsurface ML, seismic interpretation via deep learning, predictive maintenance on industrial equipment — commands a 15–25% premium at energy employers because the combination of ML skills and petroleum engineering or geoscience domain knowledge is genuinely scarce. An MLE who can also read a petrophysical log is worth more to ExxonMobil or Shell than one who cannot.

Generative AI and LLM engineering has seen sharp demand growth through 2025. Energy companies deploying LLMs over proprietary document repositories (contracts, regulatory filings, engineering reports) are paying 20–30% above baseline for engineers who can handle fine-tuning, retrieval-augmented generation, and evaluation pipelines at enterprise scale. MLOps and ML platform engineering — building the infrastructure other data scientists run on — is in consistent demand across the Houston employer mix, with typical premiums of $10,000–$20,000 above a pure modeling role at equivalent seniority.

Computer vision for medical imaging and industrial inspection is a specialized but active segment. Roles specifically requiring production CV pipelines (not just training a model in a notebook) run toward the upper end of the senior MLE band.

Total compensation breakdown

The $132,000 base median is the BLS anchor. A complete picture of mid-level MLE compensation at a major Houston employer:

Base salary: $132,000. This is the BLS-tracked figure. At energy majors and large industrial companies, base bands are relatively rigid within level — movement requires promotion, not negotiation, unless you have a competing offer.

Annual cash bonus: ~$15,000 (roughly 11% of base). Most large Houston energy and industrial employers run annual bonus programs in the 8–15% range for IC-level technical roles. At supermajors with strong earnings performance, bonus can reach 15–20% of base for senior roles. Bonus is typically tied to both individual and company performance. This is real cash — paid annually, not equity or deferred — which differentiates Houston’s energy sector from startup markets where “bonus” often means a small year-end discretionary award.

Equity/LTI: ~$20,000 annualized. This varies significantly by employer type. At energy majors, this is more likely to take the form of ESPP, pension match, or a performance share unit program than traditional RSUs. At tech-adjacent employers (HPE, Aramco Americas, publicly traded industrial companies), mid-level MLE RSU grants typically run $40,000–$80,000 over four years ($10,000–$20,000 annualized). At pre-IPO or private companies, options with significant uncertainty. Energy supermajors with no equity culture may deliver this value through pension contributions instead — a defined-benefit pension plan can be worth $30,000–$60,000 annually in actuarial terms but is invisible in standard compensation databases.

Total representative comp: ~$167,000. This is a base-centric market, not an equity-driven one. The spread on total comp is somewhat narrower than markets dominated by startup equity: P25 total comp runs around $120,000–$130,000; P90 approaches $240,000–$260,000 for staff-level roles at energy supermajors with full pension and bonus loading.

No state income tax. Texas has no individual income tax. For an engineer moving from California at a $132,000 base, this is worth approximately $11,000–$13,000 annually in reduced tax liability — not tracked in any salary database but entirely real.

Cost-of-living adjusted purchasing power

Houston’s C2ER Cost of Living Index of 94 — sourced from the Q4 2024 annual average via Houston.org’s cost-of-living comparison data — means living costs run about 6 percent below the US national average. Housing is the primary driver: Houston’s housing costs are roughly 17–20 percent below the national average despite being the fourth-largest US city by population. Two-bedroom apartments in Midtown or Montrose run $1,500–$2,100/month; comparable neighborhoods in Seattle run $2,800–$3,600, and San Francisco exceeds $4,000–$5,000 for equivalent space.

COL-adjusted comparison across key markets:

City	MLE Median Base	COL Index	Purchasing Power Equivalent
Houston	$132,000	94	$140,426
Dallas	$130,000	106	$122,642
Austin	$155,000	119	$130,252
Chicago	$112,000	107	$104,673
Seattle	$190,000	142	$133,803
San Francisco	$215,000	178	$120,787

(Purchasing power equivalent = city salary ÷ (COL index / 100))

Houston’s adjusted $140,426 leads this comparison. That’s not a quirk of the math — it reflects a market where lower living costs and no state income tax meaningfully amplify a salary that looks modest against coastal figures. The engineer choosing between a $155,000 Austin offer and a $132,000 Houston offer should run this calculation carefully: after housing and taxes, Houston can net ahead despite the lower headline number.

One honest caveat: Houston’s commuting infrastructure is car-dependent, and vehicle costs (insurance, fuel, maintenance) are above average. If you’re coming from a market where you don’t own a car, factor in a realistic transportation delta.

Three-lever negotiation playbook

Houston’s negotiation environment is different from San Francisco’s. Talent market competition is less intense at the individual employer level — most large energy and industrial employers are not in daily bidding wars for MLEs the way FAANG companies are. That means you need to construct your leverage explicitly rather than assuming the market will provide it.

Lever 1: Use the sector ladder

The most reliable source of negotiating leverage in Houston is demonstrating that you could work at a company one tier higher on the employer quality ladder. If an energy services company (Halliburton, Baker Hughes) is offering you $120,000, and you have the technical background for a supermajor role ($145,000–$165,000), interview at both. The services company offer becomes far easier to negotiate when you can credibly reference that you’re in process with Shell or ExxonMobil. You don’t need to have the supermajor offer in hand — being in late-stage conversations is enough to change the recruiter’s read of your alternatives.

The same logic applies across industries. If you’re being recruited by a hospital system at $115,000, running a parallel process with an energy services company at $130,000–$140,000 gives you a real reference point that is more persuasive than any salary data.

Lever 2: Push for title adjustment over number adjustment

Houston corporate employers — especially the large energy majors — operate with relatively rigid base bands within a given level. The recruiter often cannot move you from $132,000 to $145,000 within the same band without VP approval. But promoting you from Mid-level to Senior MLE may open a band that starts at $145,000–$150,000. That’s a $13,000–$18,000 raise achieved by reframing the conversation from “more money” to “correct leveling.”

To make this argument: document two or three examples of senior-scope work you have done. Not “I was responsible for model training” — that’s mid-level. Senior-scope looks like “I designed the feature store and serving infrastructure that three product teams now rely on” or “I defined the evaluation framework and deployment criteria for our fraud detection system that handles $X in daily transaction volume.” The specificity is what makes the case.

Lever 3: Structure the package around Houston’s comp realities

At large energy and industrial companies in Houston, base salary is often the most rigid component of an offer. Three components that are more flexible and frequently under-negotiated:

Signing bonus. Often funded from a separate budget and within recruiter authority. At a major energy company, $15,000–$30,000 is realistic for mid-to-senior MLE roles. This doesn’t hit a base band ceiling, and many candidates accept the initial offer without asking.
Accelerated review cycle. Negotiate a 6-month performance review instead of 12 months, with an explicit merit increase pathway if targets are met. If you’re starting at the lower end of a band, this creates a structured route to the midpoint without waiting a full year.
Remote flexibility. A hybrid or fully remote arrangement has real economic value in Houston’s traffic environment. It also opens geographic arbitrage: living in a lower-cost suburb (The Woodlands, Sugar Land, Katy) while maintaining the Houston pay band. Some engineers work this into a 20–30% effective pay increase through housing cost differences alone.
Professional development budget. AWS/GCP ML certifications, compute credits, and conference attendance (NeurIPS, ICML, KDD) can run $5,000–$10,000 annually in real value. Many Houston employers have this budget available but don’t advertise it.

Data caveats

No dedicated BLS occupation code for MLE. “Machine Learning Engineer” is not a BLS SOC title. The percentile figures on this page are derived from BLS OEWS May 2024 data for Houston-area Data Scientists (SOC 15-2051) — sourced via O*NET regional wage tool and the BLS Southwest region Houston metro release — adjusted for the market-documented MLE premium. The BLS Houston DS P50 is $100,420; the $132,000 MLE P50 reflects the 25–32% premium that multiple salary databases (Indeed, Built In, Glassdoor, ZipRecruiter) consistently show MLEs earning above the generalist DS baseline in this market. Where those market sources show material disagreement with each other, this page uses the midpoint.

BLS OEWS covers base wages only. The BLS figures exclude bonus, equity, pension contributions, ESPP, and LTI. For energy sector roles especially, stripping the comparison to base salary can understate total compensation by 20–40% at the senior and staff levels, where defined-benefit pension programs and meaningful bonus targets are standard.

The data is lagged. May 2024 BLS data reflects wages paid in spring 2024. The generative AI demand surge has continued through 2025. Roles explicitly requiring LLM fine-tuning, RAG architecture, or real-time inference optimization at scale are currently posting 15–25% premiums above these baseline figures in active Houston job listings.

Metro data masks intra-metro variance. The BLS Houston-Pasadena-The Woodlands MSA is a single number covering a sprawling metro. A role at a supermajor’s downtown Houston headquarters, a role at a Katy refinery analytics team, and a role at a medical center in the Texas Medical Center can have materially different pay despite falling within the same MSA. Check the specific employer and location, not just the city-level anchor.

Energy sector comp has structural non-base components. Pension, ESPP, and LTI at supermajors are difficult to compare directly with equity-heavy software company offers. A $130,000 base with a 15% pension contribution match and 15% annual bonus target has a different effective value than a $150,000 base with a 5% bonus and no pension. Model the full package, not just the salary line, and use BLS as an anchor for the base component only.

For the most current read on the Houston MLE market: use BLS OEWS as the anchor for base salary ranges, layer in Levels.fyi for employer-specific total comp data where available, and cross-reference against active LinkedIn and Indeed postings (many Houston employers voluntarily disclose salary bands even without a Texas salary transparency law).

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