Reservoir Engineer - AI Training Project
Listing checked September 18, 2026 · pay as published by Handshake AI
Overview
Handshake AI brings on energy industry experts for project-based AI research work, and this opening focuses on reservoir engineering. You will use hands-on knowledge from subsurface analysis and production operations to judge AI-generated answers, flag errors, and create expert training data. The work is remote and asynchronous, with no minimum hours; most contributors put in 5 to 20 hours each week while a project is active. Tools such as Petrel, ARIES, Techlog, Avocet, and AVEVA PI often come into play because the project values real workflow experience. You do not need prior AI experience. Placement depends on current project needs with chances to join future projects.
What You'll Do6
- 1Review AI-generated responses for accuracy, relevance, and sound engineering logic.
- 2Build expert training data that reflects real reservoir, subsurface, and production workflows.
- 3Apply hands-on tool knowledge from Petrel, ARIES, Techlog, Avocet, or AVEVA PI when judging outputs.
- 4Write clear feedback that explains why an answer misses, meets, or exceeds industry expectations.
- 5Check technical claims against reservoir engineering practices and production operations.
- 6Work on your own schedule and coordinate with AI research teams through written updates.
Requirements6
- 1At least 2 years of professional experience in reservoir engineering, subsurface analysis, or production operations.
- 2Background as a Reservoir Engineer, Petrophysicist, Production Engineer, Reserves Analyst, or a comparable energy industry role.
- 3Hands-on use of at least one tool among Petrel, ARIES, Techlog, Avocet, and AVEVA PI.
- 4Strong written communication and careful attention to technical detail.
- 5Ability to work on your own and with remote AI research teams across time zones.
- 6No prior AI experience needed.
Who Should Apply
Candidates who have at least two years in reservoir engineering, petrophysics, production engineering, or reserves analysis and who know Petrel, ARIES, Techlog, Avocet, or AVEVA PI fit the core profile. The role rewards clear writing and careful review of technical content. People who want a fixed full-time schedule or who need steady project flow may find this less suitable, because work depends on active projects and has no minimum hours. A common reason for low fit scores is listing general energy experience without showing hands-on tool use or specific reservoir workflows. Another is treating the task as simple labeling; the project expects expert judgment and detailed written feedback.
Salary Insight
The listing advertises up to $80.00 per hour. That top rate sits at the upper end for expert AI training work in specialized engineering fields, so direct experience with reservoir tools and workflows matters when the team reviews applicants. Pay is contract-based and tied to active project work, not a guaranteed full-time salary, and the source does not list a lower bound.
Pay and demand for Machine Learning & AI roles
AggregatedTypical pay
$75/hour
This role
up to $80/hr
Most Machine Learning & AI roles pay $55–$100 per hour. This role's pay falls inside that range.
Based on 626 similar roles that publish pay · 105 publish only a top rate; those count at the rate they gave
Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.
- Live similar roles
- 713
- Listed in last 30 days
- 339
- Remote
- 95%
Hiring most right now: micro1 (298) · Mercor (106) · Handshake AI (69)
Most requested skills · share of roles
- python16%
- technical writing9%
- llm evaluation7%
- ai evaluation6%
Figures from Machine Learning & AI roles live on NearSkill when this page loaded. A role can close before you apply, so check the listing itself.
Compare your resume against these rolesLocation
Compensation
Up to $80/hr
Required Skills
Application Tip
Name the exact reservoir tools you use, such as Petrel, ARIES, Techlog, Avocet, or AVEVA PI, and add a line about how many years you have used each in reservoir, subsurface, or production work. Attach a short writing sample that explains a technical decision, because the role tests written feedback as much as engineering knowledge.
See NearSkill jobs more often in your search
Application & verification flow
1Instant rubric match
Your resume is scanned against this role’s requirements to check qualification fit.
2Screened before the employer sees it
Only profiles that clear screening are passed on.
3Outcome by email
We notify you at the address on your resume once the screening is reviewed.
Similar open positions
Explore active roles that match your skills and interests.
Handshake AI
VerifiedProduction Engineer - Remote AI Fellowship
Handshake AI seeks production engineers and related energy specialists to review AI-generated material and shape training data for models used in subsurface work. You will apply hands-on knowledge of reservoir engineering, subsurface analysis, and production operations to judge whether AI responses match real industry practice. The engagement runs as a part-time fellowship with remote, asynchronous hours, so you can fit it around another role. No AI background is necessary, and active projects ask for about 5 to 20 hours per week.
Handshake AI
VerifiedSubsurface Reservoir Engineer - Remote Fellowship
Handshake AI seeks subsurface and reservoir specialists for part-time contract projects that feed energy-industry AI training sets. You will create expert outputs such as reservoir simulation studies, SEC reserves reports, well test analyses, and production allocation calculations. The work uses Petrel, ARIES, Techlog, and Avocet in the same way you would handle daily engineering tasks. No fixed hours or minimum schedule apply, so you can take on assignments alongside a current role.
Handshake AI
VerifiedDrilling/Production Engineer - Energy AI (Remote)
Handshake AI hires energy professionals for project-based work that improves how AI systems handle industrial operations and performance engineering questions. You bring your experience with tools like AVEVA PI, WinCC, or Power BI to judge AI-generated answers and build expert training data. The schedule stays remote and async, with most contributors logging 5 to 20 hours per week during an active project. No prior AI work is needed, and you can take on the fellowship alongside your current role.
Handshake AI
VerifiedReliability Engineer - Remote Energy AI Project
Handshake AI seeks energy professionals to join a remote, part-time fellowship that brings real operations knowledge into AI research. You review AI-generated answers, flag errors, and craft expert training data using your own experience with plant performance, industrial operations, or energy asset management. The schedule is async, and most contributors log 5 to 20 hours per week during active projects. You do not need prior AI experience. The project runs as long as client needs continue, and strong contributors may get picked for later assignments.
Handshake AI
VerifiedEnergy Professional - Remote AI Evaluation
Handshake AI hires energy specialists for project-based AI work, not a permanent role. You bring hands-on experience from oil and gas, power generation, utilities, renewables, or energy compliance and use it to judge AI-generated content. The job centers on reviewing model answers for accuracy and relevance, then explaining how real energy workflows operate in practice. No AI background is required. Work happens remote on an asynchronous schedule, with most contributors logging around 5 to 20 hours each week while a project is active.
Handshake AI
VerifiedPlant Performance Engineer - Remote Contract
Handshake AI hires energy professionals for project-based contract work that improves how AI models handle industrial operations. You bring your own experience with plant performance, energy asset management, or reliability work and use it to judge AI-generated answers for accuracy and relevance. Your daily tools matter here: AVEVA PI, WinCC, Power BI, and similar platforms give you the context to create expert training data and flag gaps. The schedule stays flexible, with most contributors putting in 5 to 20 hours each week and no minimum hour requirement. You can join active projects when needs match your background.