ML Engineer Jobs in Energy: Demand, Pay & Skills
Part of Plutarch’s ongoing analysis of skill demand in energy hiring — last updated 5 October 2026, based on 31 tracked postings.
As of 5 October 2026, Plutarch tracked 31 unique open ML Engineer postings at energy employers. 5 postings disclosed annual pay, with a United States median of USD 198,000.
This is a small, geographically concentrated market for ML Engineer roles, with the large majority of postings based in the United States and a much smaller number spread across India, Japan, Saudi Arabia, and Switzerland. Seniority skews heavily toward senior and above, with an equal number of titles giving no level signal at all, while junior and executive-level openings are each represented only once. Titles show a mix of infrastructure-focused, perception-focused, and general machine learning engineering work.
Open postings
Where
- United States · 16
- India · 6
- Romania · 3
- United Kingdom · 3
- Denmark · 1
- Other or not stated · 2
Seniority
- Early career · 1
- Level not stated in title · 15
- Senior, lead, staff or manager · 14
- Leadership · 1
Disclosed pay by country · annual
| Country | Lowest to highest employer midpoint | Median | Postings stating pay |
|---|---|---|---|
| United States | USD 130,000–222,000 | USD 198,000 | 5 of 13 |
Directional, not conclusive. Each figure is the midpoint of a salary range an employer disclosed in a public job posting, derived from public market sources and rounded to the nearest thousand. Samples are small, so a country appears only when at least 5 open postings disclose annual pay. At these sample sizes, do not compare one role’s median against another’s — the difference between them is smaller than the error on either.
How many employers state pay
- United States · pay stated in 8 of 13 postings we could read
- India · pay stated in 0 of 5 postings we could read
- Romania · pay stated in 0 of 3 postings we could read
- United Kingdom · pay stated in 0 of 3 postings we could read
- Denmark · pay stated in 0 of 1 posting we could read
Counted from the same open postings as above, leaving out postings whose text we could not read for pay. Pay disclosure tracks local pay-transparency law more closely than employer policy, so a low rate is not evidence that employers here pay less.
Who is hiring
| Employer | Open postings |
|---|---|
| S&P Global | 6 |
| Siemens Energy | 5 |
| Lucid Group | 4 |
| Argus Media | 2 |
| Gridware | 2 |
| Ascend Analytics | 1 |
| Baker Hughes | 1 |
| bp | 1 |
| Chevron | 1 |
| Focused Energy | 1 |
| Gridmatic | 1 |
| Kpler | 1 |
| Other employers | 5 |
How these roles are titled
The titles employers use for this role, most repeated first. Titles shown without a count appeared once.
- Machine Learning Engineer · 4 postings
- Senior Machine Learning Engineer · 3 postings
- AI/ML Engineer · 2 postings
- Staff Machine Learning Engineer · 2 postings
- AI /ML Solutions Engineer
- AI/Machine Learning Engineer
- Associate Director, Machine Learning Engineering
- Experienced AI/ML Engineer
- Machine Learning Engineer - Summer Intern 2027
- Machine Learning Engineer II
- Machine Learning Operations Engineer II
- Member of Technical Staff, ML Engineer
- ML Engineer - Power
- ML Infrastructure Engineer
- MLOps Team Lead
What employers ask for
Skills and tools named in the text of 25 open postings we could read in full, most named first.
| Skill or tool | Postings naming it | Employers |
|---|---|---|
| Python | 25 of 25 | 14 |
| Machine learning | 21 of 25 | 12 |
| PyTorch | 15 of 25 | 7 |
| AWS | 14 of 25 | 9 |
| LLMs | 12 of 25 | 7 |
| CI/CD | 11 of 25 | 10 |
| MLOps | 11 of 25 | 9 |
| Statistics | 10 of 25 | 9 |
| Docker | 9 of 25 | 7 |
| Generative AI | 9 of 25 | 6 |
| Kubernetes | 8 of 25 | 8 |
| AI agents | 8 of 25 | 5 |
| Git | 8 of 25 | 5 |
| Airflow | 7 of 25 | 6 |
| TensorFlow | 7 of 25 | 6 |
A skill counts when the posting names it anywhere — requirements, role description or the employer’s own introduction. A skill is shown only when at least 3 postings from at least two employers name it. Postings whose full text we did not read are left out of these counts rather than counted as asking for nothing.
Patterns in the job titles
- Perception-focused machine learning engineering
- Machine learning infrastructure engineering
ML Engineer job description template
An outline to start from. The requirements are the skills energy employers most often name for this role, with how often each is named — not a model's guess.
Already have a draft? Paste it for a hiring-feasibility brief and a sharpened version. For the credential line, see which credentials the law requires, and where.
What the postings suggest about filling this role
The heavy tilt toward senior, lead, principal, staff, and manager titles alongside almost no junior openings suggests employers are competing for a narrow pool of experienced candidates, which tends to make filling these roles harder. The concentration of postings in one country plus repeated perception and infrastructure specializations further narrows the qualified candidate pool relative to a more evenly distributed or generalist market.
Read from employer demand only. These sources show what employers advertise, not how many people are available to hire, so this is a reading of the vacancies rather than a measure of scarcity.
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Check your role — two briefs freeCounts are unique open postings seen in the last three weeks, taken from the named employers’ own published job postings; a vacancy posted in several places is counted once. Employers are named because they published these postings publicly themselves. The written summary is AI-generated from those postings and contains no figures and no employer names. Posting figures are direct counts; pay figures are the median and range of the salaries those employers disclosed. Terms of use.