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Full Time Ai Training For Physics Jobs (NOW HIRING)

UniversalAGI

AI Product Engineer

San Francisco, CA · On-site

San Francisco | Work Directly with CEO & founding team | Report to CEO | OpenAI for Physics | 5 Days Onsite AI Product Engineer Location: Onsite in San Francisco Compensation: Competitive Salary ...

Agap Technologies

Generative AI Training

Atlanta, GA · On-site

Our Training Features: • You will receive top quality instruction that is famous for Online ... AI training. . Provide OPT Stem Ext.: Guidance and support for applying for the 24-month OPT STEM ...

Kanshe Infotech

Generative AI Training

Raleigh, NC · On-site

Our Training Features: • You will receive top quality instruction that is famous for Online ... AI. . Provide OPT Stem Ext.: Guidance and support for applying for the 24-month OPT STEM extension

Kanshe Infotech

Generative AI Training

Raleigh, NC · On-site

You will receive top quality instruction that is famous for Online IT training. Trainees will ... We are offering online training on Generative AI. . Provide OPT Stem Ext.: Guidance and support for ...

Prolific

AI Training Experts - Gilbert, US

Required : • AI Training task skills and verifiable professional experience as an AI Trainer • A willingness to take our skills verification test to assess your suitability for our participant ...

UniversalAGI

Technical Product Manager

San Francisco, CA · On-site

$196K - $227K/yr

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 ...

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Full Time Ai Training For Physics information

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$46.9K

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How much do full time ai training for physics jobs pay per year?

As of Aug 7, 2026, the average yearly pay for full time ai training for physics in the United States is $46,902.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,500.00 and $50,500.00 per year, depending on experience, location, and employer.

What is the difference between Full Time Ai Training For Physics vs Data Scientist?

AspectFull Time Ai Training For PhysicsData Scientist
Required CredentialsPhysics degree, programming skills, AI knowledgeStatistics, programming, domain expertise
Work EnvironmentResearch labs, tech companies, academiaCorporate offices, tech firms, consulting
Industry UsageAI development, physics simulations, researchData analysis, predictive modeling, business insights

Full Time Ai Training For Physics focuses on applying AI techniques to physics problems, requiring a physics background and AI skills. Data Scientists analyze data to extract insights across industries. While both roles involve programming and data handling, Full Time Ai Training For Physics emphasizes physics applications, whereas Data Scientists work across diverse sectors.

More about Full Time Ai Training For Physics jobs
What are the most commonly searched types of Ai Training For Physics jobs? The most popular types of Ai Training For Physics jobs are:
What job categories do people searching Full Time Ai Training For Physics jobs look for? The top searched job categories for Full Time Ai Training For Physics jobs are:
Full Time Ai Training For Physics jobs near you
Infographic showing various Full Time Ai Training For Physics job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 17% Part Time, and 2% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution, with an average salary of $46,902 per year, or $22.5 per hour.

AI Product Engineer

UniversalAGI

San Francisco, CA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 22 days ago

Job description

San Francisco | Work Directly with CEO & founding team | Report to CEO | OpenAI for Physics | 5 Days Onsite
AI Product Engineer
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
UniversalAGI is hiring an AI Product Engineerto own our customer facing product across the entire stack. In this role, you will build and own the end-to-end platform that engineers use to train and host physics models. This includes managing everything from data generation and storage to creating reusable templates and building a delightful user interface.
You'll work closely with the CEO and founding team to turn research into repeatable, scalable, reliable systems - internally and in customer infrastructure. This is a "ship outcomes" role: your work directly determines how fast we can iterate, how reproducible our results are, and how reliably we deliver in production.
What You'll Do
  • Ship End-to-End: Own and ship features across the full stack, including frontend, backend, databases, cloud services, APIs, and the UI
  • Enable Physics Workflows: Build seamless capabilities that take engineering customers from raw data input to a fully hosted, functioning surrogate model
  • Design Core Abstractions: Build clean, reusable templates so power users can move fast, while ensuring new users can get started in minutes
  • Iterate on Feedback: Collect user feedback, iterate rapidly, and maintain strict product reliability and backwards compatibility as we scale our customer base
  • Collaborate Globally: Partner hand-in-hand with the founding team and engineering leadership to define product scope and architecture

Qualifications
  • End-to-End Production Ownership: Proven track record of shipping customer-facing products, with deep ownership over frontend, backend, and database layers
  • Strong SWE Fundamentals: Excellent intuition for clean componentization, organized code architectures, user experience, and visual design
  • Stack Fluency: Deep technical comfort with Python on the backend, alongside React, TypeScript, and Next.js on the frontend. Comfortable navigating databases and cloud APIs. PyTorch is not required
  • Product Instinct: Ability to hold the user journey clearly in your head while evaluating complex technical tradeoffs

Bonus Qualifications
  • AI/ML Integration: Hands-on experience integrating AI components into customer products (e.g., LLMs, agents, or ML-backed product features)
  • Domain Context: Prior experience or background with 3D applications, CAD, physics simulations, or engineering tooling domains
  • Startup DNA: Prior early-stage startup experience (0 to 1 product development)

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 publishing papers
  • 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 model decisions 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
  • Bias for Action: Ships experiments fast, learns from failures, and iterates quickly

What We Offer
  • Opportunity to define the future of physics AI from the ground up
  • Work on cutting-edge problems at the intersection of deep learning and physics simulation
  • 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 train the models that will revolutionize physics simulation, push the boundaries of what AI can learn, and deliver real impact, UniversalAGI is the place for you.

Apply