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Remote Simulation Software Engineer Jobs (NOW HIRING)

Hitachi

Simulation Engineer

Holland, MI · On-site +1

Engineering & Science Job Schedule: Full time Remote: No The Opportunity: JR Automation, a Hitachi ... Experience with robotic and/or discrete simulation software preferred, software such as: o ...

Hitachi

Simulation Engineer

Holland, MI · On-site +1

Engineering & Science Job Schedule: Full time Remote: No The Opportunity: JR Automation, a Hitachi ... Experience with robotic and/or discrete simulation software preferred, software such as: o ...

FOUR SQUARED SOLUTIONS

Software Engineer

Orlando, FL · Remote

... a remote opportunity with limited on-site meetings in Orlando, FL The Senior Software Engineer plays a critical role in the design, development, and testing of advanced simulation and training ...

GeoDelphi

Software Engineer

Alexandria, VA · Remote

Software Engineer Location: Remote / Alexandria, VA Clearance: Active TS/SCI or eligibility to be ... remote sensing, GEOINT, or commercial geospatial data. * Experience with population simulation ...

GeoDelphi

Software Engineer

Alexandria, VA · Remote

Software Engineer Location: Remote / Alexandria, VA Clearance: Active TS/SCI or eligibility to be ... remote sensing, GEOINT, or commercial geospatial data. * Experience with population simulation ...

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Remote Simulation Software Engineer information

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$74K

$137.8K

$197K

How much do remote simulation software engineer jobs pay per year?

As of Jun 19, 2026, the average yearly pay for remote simulation software engineer in the United States is $137,846.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,000.00 and $162,000.00 per year, depending on experience, location, and employer.

What is the difference between Remote Simulation Software Engineer vs Remote Data Analyst?

AspectRemote Simulation Software EngineerRemote Data Analyst
Required CredentialsBachelor's in Computer Science, Engineering, or related field; programming skills in C++, Python; experience with simulation toolsBachelor's in Statistics, Mathematics, or related; proficiency in SQL, Excel, data visualization tools
Work EnvironmentDeveloping and testing simulation models remotely, often collaborating with engineering teamsAnalyzing datasets remotely, creating reports, and providing insights for business decisions
Employer & Industry UsageTech, automotive, aerospace, manufacturing industriesFinance, marketing, healthcare, retail sectors

While both roles involve remote work and data handling, Remote Simulation Software Engineers focus on creating and refining simulation models using programming and engineering principles. In contrast, Remote Data Analysts interpret data to inform business strategies. The roles share some technical skills but differ in their core functions and industry applications.

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Remote Simulation Software Engineer jobs near you
Sr. Software Engineer, Simulation, tvScientific

Sr. Software Engineer, Simulation, tvScientific

Pinterest

San Francisco, CA • Remote

Other

Posted 26 days ago

Job description

About tvScientific

tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.

We are seeking a Sr. Software Engineer to build out our simulation and AI capabilities. You'll design and implement systems that model the CTV advertising ecosystem - auction dynamics, bidding strategies, campaign outcomes, and counterfactual scenarios - and develop AI-driven tools that accelerate how we build, test, and deploy ML systems.


What you'll do:

  • Design and build simulation environments that model CTV auction mechanics, inventory supply, and advertiser competition
  • Develop counterfactual and what-if frameworks for evaluating bidding strategies, budget allocation, and pacing algorithms offline
  • Build AI agents that explore strategy spaces, generate hypotheses, and automate experimentation within simulated environments
  • Use simulation to de-risk ML model deployments - validate new bidding and optimization strategies before they touch live traffic
  • Define the technical direction for simulation and AI infrastructure and mentor engineers on the team


What we're looking for:

  • Systems programming experience in Zig or similar (C, C++, Rust)
  • Deep understanding of probabilistic modeling, stochastic processes, or agent-based simulation
  • Hands-on experience with modern AI tools: LLMs, code generation, agentic workflows - and good judgment about when they help vs. when they don't
  • Adtech experience: you understand RTB mechanics, and the dynamics of programmatic advertising
  • Ability to translate business questions ("what happens if we change our bid strategy?") into rigorous simulation frameworks
  • Clear written communication: you'll be defining new technical directions and need to bring others along
  • Ownership: you scope, design, and ship systems end-to-end with minimal direction
  • Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
  • Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
  • High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.
  • Bachelor's degree in computer science, machine learning, statistics, a related field or equivalent experience
  • Nice-to-Haves:
    • Strong production Python skills and experience building simulation or modeling systems
    • Causal inference - uplift modeling, synthetic controls, difference-in-differences, or incrementality testing
    • Experience with discrete event simulation, Monte Carlo methods, or digital twins
    • Reinforcement learning - using simulated environments for policy learning and evaluation
    • Experience building agentic AI systems or multi-agent simulations
    • Big data experience with Scala and Spark
    • MLOps experience - model deployment, monitoring, and pipeline orchestration on AWS

In-Office Requirement Statement:

  • We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.


Relocation Statement:

  • This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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