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Flexible Monte Carlo Simulation Jobs (NOW HIRING)

Fuse

Nuclear Engineer

San Leandro, CA · On-site

$111K - $133K/yr

We are seeking a Nuclear Engineer with expertise in particle transportation, Monte Carlo simulation, and radiation shielding to support our fusion facility. The ideal candidate will have a strong ...

Actalent

GNC Simulation Software Engineer

Houston, TX

$55 - $80/hr

Conduct Monte Carlo analyses and sensitivity studies to validate robustness and reliability. Validate simulation models against test data and engineering expectations. Use programming languages ...

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Flexible Monte Carlo Simulation information

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$11K

$67.6K

$121.5K

How much do flexible monte carlo simulation jobs pay per year?

As of Aug 7, 2026, the average yearly pay for flexible monte carlo simulation in the United States is $67,601.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,000.00 and $79,500.00 per year, depending on experience, location, and employer.

What is the difference between Flexible Monte Carlo Simulation vs Quantitative Analyst?

AspectFlexible Monte Carlo SimulationQuantitative Analyst
Required CredentialsDegree in Mathematics, Statistics, or Finance; programming skillsDegree in Finance, Economics, Mathematics; certifications like CFA often preferred
Work EnvironmentFinancial institutions, risk management, modeling teamsInvestment banks, asset management firms, hedge funds
Industry UsageUsed for risk analysis, option pricing, and financial modelingDevelops models, analyzes financial data, advises on investments

Flexible Monte Carlo Simulation specialists focus on implementing simulation techniques for risk and financial modeling, often requiring programming skills and quantitative knowledge. Quantitative Analysts develop financial models and analyze data to support investment decisions. While both roles require strong quantitative skills, the Monte Carlo Simulation role emphasizes simulation techniques, whereas Quantitative Analysts focus on broader financial analysis and strategy.

What is a flexible Monte Carlo simulation?

A Flexible Monte Carlo Simulation is a computational technique used to model the probability of different outcomes in a process that cannot easily be predicted due to the intervention of random variables. Unlike traditional Monte Carlo simulations, flexible versions allow for dynamic adjustments to model parameters, scenarios, or distributions during the simulation process. This adaptability makes them particularly useful for complex systems where conditions or inputs may change over time. Flexible Monte Carlo Simulations are widely used in fields such as finance, engineering, and risk management to better understand uncertainty and make informed decisions.

What are the key skills and qualifications needed to thrive as a Monte Carlo simulation specialist, and why are they important?

To thrive as a Monte Carlo Simulation Specialist, you need a solid background in mathematics, statistics, probability theory, and a relevant degree in a quantitative field such as mathematics, physics, engineering, or finance. Familiarity with simulation software (such as MATLAB, R, Python, or specialized Monte Carlo tools) and experience with statistical programming are typically required. Strong analytical thinking, attention to detail, and effective communication skills help professionals interpret results and present findings clearly to stakeholders. These skills are crucial to ensure accurate modeling, risk assessment, and informed decision-making across various industries.

What are common challenges faced by professionals working with flexible Monte Carlo simulation models, and how can they be addressed?

Professionals working with flexible Monte Carlo simulation models often encounter challenges such as computational complexity, managing large datasets, and ensuring the accuracy of input assumptions. To address these issues, it's important to develop efficient algorithms, utilize high-performance computing resources, and collaborate closely with subject-matter experts to validate model parameters. Additionally, regular code reviews and sensitivity analyses can help identify potential pitfalls and improve model reliability.
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Flexible Monte Carlo Simulation jobs near you
Infographic showing various Flexible Monte Carlo Simulation job openings in the United States as of August 2026, with employment types broken down into 86% Full Time, and 14% Contract. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $67,601 per year, or $32.5 per hour.

Senior Software Engineer

Odyssey Systems Consulting Group, Ltd.

Colorado Springs, CO • On-site

$122K - $161K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 10 days ago

Job description

Position Summary

We are seeking a Senior Software Engineer to be a primary technical contributor on the Multimode Threat Engagement Simulation Platform. You will own significant portions of the stack end-to-end - building the Julia computation backend, the React/TypeScript/CesiumJS frontend, and the CI/CD pipeline that delivers standalone Windows and Linux artifacts - with a primary emphasis on high-performance and scientific computing. You will work closely with the Lead Engineer on architecture decisions and with domain engineers (RF, EO/IR) to implement their physics models in a performant, maintainable form.

This role demands genuine depth in high-performance compute application development. The backend is not a conventional web API - it runs trajectory integration, Monte Carlo simulation across thousands of runs, and real-time surrogate model inference. You should be comfortable profiling and optimizing numerical code, reasoning about parallelism, and making informed trade-offs between simulation fidelity and throughput.

***Contingent upon contract award***

Responsibilities

High-Performance Computation Backend

  • Implement and optimize the Julia physics computation server: trajectory integration (RK4/RK45 schemes via DifferentialEquations.jl), SGP4 orbital propagation (SatelliteToolbox.jl), and Monte Carlo driver with Threads.@threads parallelism
  • Profile and optimize computation-critical paths; benchmark throughput and latency against program requirements (e.g., 10,000 Monte Carlo runs within a defined wall-clock target)
  • Integrate ONNX.jl surrogate model inference for real-time parameter sweep capabilities; ensure inference latency meets the <1ms interactive target
  • Implement CZML generation from physics outputs - trajectory arcs, satellite orbital paths, coverage footprints - for time-dynamic Cesium visualization
  • Design and maintain the mission data model: JSON serialization, versioned file format with backward compatibility, and cross-platform path handling for Windows and Linux
  • Implement the HTTP.jl API layer with well-defined request/response schemas, appropriate error handling, and structured logging

Frontend and Visualization

  • Build React/TypeScript components for the mission planning interface: tabbed mission overview, asset and task tree views, mission parameter forms, and the analysis panel
  • Integrate and maintain the CesiumJS/Resium 3D globe: asset markers, trajectory rendering, satellite ground tracks, coverage footprints, and CZML-driven animation with the Cesium timeline
  • Manage frontend application state (mission data, UI state, async physics query results) using appropriate state management patterns for a data-heavy desktop application
  • Implement data-driven analysis visualizations - trajectory plots, Pk curves, Monte Carlo distribution charts - using Recharts, Plotly.js, or equivalent

DevOps and Cross-Platform Packaging

  • Maintain the CI/CD pipeline in GitHub Actions: automated builds producing Windows NSIS installers and Linux AppImages from a single codebase
  • Manage PackageCompiler.jl sysimage builds for the Julia physics server binary on both target platforms
  • Maintain electron-builder configuration and platform-specific packaging scripts; validate installer behavior on clean Windows and Linux test environments
  • Implement build-time embedding of ONNX model files and asset resources; manage versioning of bundled artifacts

***Contingent upon contract award***

Qualifications

Citizenship: Must be a US citizen

Minimum Required Qualifications

Clearance: Active Secret Clearance

Education: B.S. in Computer Science, Software Engineering, Electrical Engineering, Physics, or related STEM field

Years of Experience: 5+ years of software development experience, with demonstrated depth in at least one of the following areas: scientific computing, numerical simulation, high-performance computing, or data-intensive desktop applications

Certifications: NA

Additional Skills

  • Proficiency in TypeScript/React or equivalent modern frontend framework
  • Experience with a compiled or JIT-compiled high-performance language (Julia, C++, Rust, Fortran, or Python with NumPy/Numba/Cython extensions)
  • Understanding of parallel computing patterns relevant to numerical workloads: thread-level parallelism, SIMD, memory-access optimization
  • Experience with REST API design and implementation as a client-server boundary within a single-machine application

Preferred Qualifications

Clearance: Active TS/SCI

Education: MS degree 

Certifications: NA

Preferred Skills

  • Direct experience with Julia and the SciML / DifferentialEquations.jl ecosystem; PackageCompiler.jl sysimage generation
  • Experience with CesiumJS, Resium, and CZML for 3D geospatial visualization
  • Familiarity with orbital mechanics, trajectory simulation, or atmospheric modeling at an implementation level (not just theoretical)
  • Experience with ONNX Runtime, ONNX.jl, or equivalent ML inference frameworks
  • Experience with Electron and electron-builder for cross-platform desktop deployment
  • Familiarity with at least one sensor or physics domain: radar detection, EO/IR performance, acoustic propagation, or multi-sensor tracking - at the level of understanding model inputs/outputs and integrating them correctly

Additional Information

Location: Colorado Springs, CO or Boston, MA

Travel: Approx. 15-20%

Remote, Onsite, or Hybrid: Hybrid

#LI-JK1

***Contingent upon contract award***

Company Overview

Odyssey is a world-class technical, engineering, and integration company serving the warfighting ecosystem with airborne integration, ISR, C2, and warfighter readiness capabilities. Odyssey meets the military's operational needs by integrating layered defense systems from equipment, technology, and services to data, information, and business operations. We streamline defense acquisition and sustainment, engineering the technical battlefield with domain-specific proficiency to ensure lethality. Odyssey is dedicated to excellent contract execution, peak organizational performance, and fostering a workplace built on employee care.

Odyssey is proud to live out our core values of commitment, ambition, and respect in our work and communities through OdysseyCares, a philanthropic group focused on giving back through direct donations, an employer match program, and volunteering events.

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities

Please Note:

Final compensation for this position will be determined by various factors such as the Federal Government contract labor categories and contract wage rates, relevant work experience, specific skills and competencies, geographic location, education, and certifications.

This position is filled through continuous recruitment and will remain open until a sufficient pool of applications has been received.Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, Tricare supplement, short-term disability, long-term disability, 401(k) match, flexible spending accounts, health savings accounts, employee assistance program, learning and development benefit, paid time off, and holidays.Odyssey Benefits

Employment Type: FULL_TIME

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