Reservoir Simulation Engineer

📍 San Francisco 🏢 5 Days Onsite

Location: Onsite in San Francisco

Compensation: Competitive Salary + Equity

Reservoir Simulation Engineer

Who We Are

Engineering simulation is one of the last major categories of software that AI hasn't rebuilt. The tools used to simulate aircraft, ships, reservoirs, and medical devices still run on numerical methods that are decades old, and an engineer can wait a full day for a single answer. UniversalAGI is building foundation models that learn physics directly from data, and they are already running in early deployments on real computational fluid dynamics and reservoir engineering problems for some of the largest industrial and defense organizations in the world.

We are a team of 25 researchers and engineers in San Francisco backed by Elad Gil (#1 Solo VC), Eric Schmidt (former Google CEO), Prith Banerjee (ANSYS CTO), Ion Stoica (Databricks Founder), Jared Kushner (former Senior Advisor to the President), David Patterson (Turing Award Winner), and Luis Videgaray (former Foreign and Finance Minister of Mexico).

About the Role

As a Reservoir Simulation Engineer, you'll be in the arena from day one, building the future of AI for physics simulation with your own hands. This is your chance to take everything you've learned building, running, and history-matching reservoir models, conventional and unconventional alike, and use it to generate the high-fidelity simulation data that trains our foundation models for subsurface flow.

You'll work directly with the CEO and founding team to shape our product around the real pain points you've faced in your career: the weeks lost building and history-matching reservoir models, the manual handoff between geologic modeling and dynamic simulation, and the limits of a single deterministic forecast when the subsurface is anything but certain.

What You'll Do

Design, build, and run reservoir simulation studies, both blackoil and compositional models, across conventional and unconventional reservoirs, at unprecedented scale and speed

Come up with creative ways to construct reservoir models, simulate hundreds or thousands of reservoir model variants systematically, building the data pipelines that will train our foundation models

Guide the development of our product and our revolutionary new AI models for physics by working directly on research problems with our AI team, bridging the gap between traditional reservoir simulation and cutting-edge ML

Work directly with clients to solve their problems and define benchmark datasets, validation criteria, and workflows that prove our models can match or exceed traditional reservoir simulation accuracy

Generate high-quality simulation data at scale; every simulation you run directly improves our foundation models

Advise the AI research team on the nuances that matter: PVT behavior and fluid characterization, relative permeability and capillary pressure, history matching and uncertainty quantification, multi-stage hydraulic fracturing and complex fracture networks, and the production-decline behavior that separates unconventional reservoirs from conventional ones

Lead technical customer conversations with customers and internal teams, translating between the world of reservoir engineering and the world of AI

Qualifications

3-5+ years of industry hands-on experience building and running reservoir simulation models, including conventional (blackoil and compositional) and unconventional reservoirs, from model construction through history matching, forecasting, and optimizing field development

Expert in reservoir simulation frameworks (Eclipse/Intersect, CMG, OPM Flow, or similar), including blackoil and compositional formulations

Deep understanding of reservoir engineering fundamentals: PVT behavior, relative permeability and capillary pressure, well modeling, material balance, and history matching

Solid understanding of the static-to-dynamic model handoff: geologic and geocellular model construction, upscaling, and grid generation

Strong communicator capable of bridging customers, engineering and research teams

Outstanding execution velocity and delivery

Exceptional creativity, problem-solving ability, ambition, and attention to detail

Comfortable working in high-intensity, fast-paced startup environments with evolving priorities and tight deadlines

Bonus Qualifications

Working proficiency in Python (or similar) for scripting, automating simulation pipelines, and structuring simulation output into clean, well-labeled datasets

Prior experience integrating AI/ML models into reservoir workflows, or generating simulation datasets specifically intended to train or validate machine learning models

Experience with probabilistic or ensemble history matching, uncertainty quantification, or geostatistical modeling (Gaussian processes, kriging)

Experience modeling unconventional reservoirs: multi-stage hydraulic fracturing, complex fracture networks, and the production-decline behavior distinct from conventional plays

Master's or PhD in Petroleum Engineering, Reservoir Engineering, Geology, or a related field

Domain expertise in geothermal, or other subsurface flow applications adjacent to oil and gas

Experience at high-growth AI startups (Seed to Series C)

Forward deployed experience working directly with customers to solve their hardest problems

Cultural Fit

Technical Respect : Ability to earn respect through hands-on technical contribution

Intensity : Thrives in our unusually intense culture - willing to grind when needed

Customer Obsession : Passionate about solving real customer problems, not just cool tech

Deep Work : Values long, uninterrupted periods of focused work over meetings

High Availability : Ready to be deeply involved whenever critical issues arise

Communication : Can translate complex technical concepts to customers and team

Growth Mindset : Embraces the compounding returns of intelligence and continuous learning

Startup Mindset : Comfortable with ambiguity, rapid change, and wearing multiple hats

Work Ethic : Willing to put in the extra hours when needed to hit critical milestones

Team Player : Collaborative approach with low ego and high accountability

What We Offer

Opportunity to shape the technical foundation of a rapidly growing foundational AI company.

Work on cutting-edge industrial AI problems with immediate real-world impact.

Direct collaboration with the founder & CEO and ability to influence company strategy

Competitive compensation with significant equity upside.

In-person first culture - 5 days a week in office with a team that values face-to-face collaboration.

Access to world-class investors and advisors in the AI space.

Benefits

We provide great benefits, including:

Competitive compensation and equity.

Competitive health, dental, vision benefits paid by the company.

401(k) plan offering.

Flexible vacation.

Team Building & Fun Activities.

Great scope, ownership and impact.

AI tools stipend.

Monthly commute stipend.

Monthly wellness / fitness stipend.

Daily office lunch & dinner covered by the company.

Immigration support.

How We’re Different

“ The credit belongs to the man who is actually in the arena, whose face is marred by dust and sweat and blood; who strives valiantly; who errs, who comes short again and again... who at the best knows in the end the triumph of high achievement, and who at the worst, if he fails, at least fails while daring greatly." - Teddy Roosevelt

At our core, we believe in being “in the arena.” We are builders, problem solvers, and risk-takers who show up every day ready to put in the work: to sweat, to struggle, and to push past our limits. We know that real progress comes with missteps, iteration, and resilience. We embrace that journey fully knowing that daring greatly is the only way to create something truly meaningful.

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