Founding Reservoir Engineer / Reservoir Geologist (Modeling & Simulation)

📍 San Francisco | Work Directly with CEO & founding team | Report to CEO | OpenAI for Physics | 🏢 5 Days Onsite

Founding Reservoir Engineer / Reservoir Geologist (Modeling & Simulation)

Location: Onsite in San Francisco

Compensation: Competitive Salary + Equity

Who We Are

UniversalAGI is building OpenAI for Physics. AI startup based in San Francisco and 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). We’re building foundation AI models for physics that enable end-to-end industrial automation from initial design through optimization, validation, and production.

We're building a high-velocity team of relentless researchers and engineers that will define the next generation of AI for industrial engineering. If you're passionate about AI, physics, or the future of industrial innovation, we want to hear from you.

About the Role

As a founding Reservoir Engineer / Geologist, 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 in reservoir geology and use it to build foundation AI models that will transform how the entire industry works.

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 tedious data preparation, the manual grid and upscaling loops, and endless history-matching.

What You'll Do

• Design, preprocess, grid, simulate, and post-process reservoir models (geological and flow) at unprecedented scale and speed, using industry-standard simulators and real subsurface data.

• Develop systematic workflows to generate hundreds or thousands of reservoir scenarios, including geological realizations, well configurations, and operating conditions—building the data pipelines that will train our foundation models.

• Guide the development of our product and our AI models for physical systems by working directly on research problems with our AI team, bridging the gap between traditional reservoir simulation and modern machine learning.

• Work directly with clients to define benchmark datasets, validation criteria, and end-to-end workflows that demonstrate our models can match or exceed conventional reservoir simulation accuracy and decision value.

• 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 in subsurface modeling: model fidelity, black-oil vs compositional vs thermal models, gridding and upscaling tradeoffs, relative permeability, well controls, and numerical stability.

• Lead technical conversations with customers and internal teams, translating between the language of reservoir engineering / geology and the world of AI and foundation models.

• This role is for someone ready to push beyond the limits of traditional reservoir simulation, tackle deep uncertainty and scale challenges, and help define the next generation of subsurface engineering and decision-making.

Qualifications

• M.S. or Ph.D. in Reservoir Engineering, Petroleum Engineering, Geology/Geoscience, or closely related field (required).

• 3+ years of hands-on industry experience doing reservoir modeling and reservoir simulation end-to-end, ideally in an operator, service company, or subsurface consultancy setting.

• Expert in reservoir simulator frameworks (e.g., SLB ECLIPSE / INTERSECT, CMG (IMEX/GEM/STARS), tNavigator, Nexus, or similar) and comfortable working directly with simulation decks / control files.

• Deep understanding of subsurface flow and numerical simulation: multiphase Darcy flow, PVT, relative permeability & capillary pressure, well modeling/controls, initialization, boundary conditions, convergence/stability, and common failure modes.

• Experience with model building and conditioning: gridding, upscaling, faults/barriers, contacts, rock/fluid property population, and rigorous QC to ensure simulation-ready inputs.
Ability to design and execute systematic scenario studies (sensitivities, uncertainty ensembles, development plan variants) and produce clean, explainable outputs that can serve as ground truth for ML.

• Ability to design and execute systematic scenario studies (sensitivities, uncertainty ensembles, development plan variants) and produce clean, explainable outputs that can serve as ground truth for ML.

• Outstanding execution velocity and delivery, with strong attention to detail and a data-quality mindset.

• 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

• Prior experience integrating AI/ML (or proxy/surrogate models) into subsurface workflows, or partnering with ML teams to define training targets and validation.

• Experience at high-growth AI / deep-tech startups (Seed to Series C) or in a forward-deployed / client-facing technical role.

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.

If you're ready to join the future of physics simulation, push creative boundaries, and deliver impact, UniversalAGI is the place for you.