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Physics Simulation Python Jobs in Miami, FL (NOW HIRING)

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Physics Simulation Python information

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$10.5K

$64.7K

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How much do physics simulation python jobs pay per year?

As of Sep 13, 2026, the average yearly pay for physics simulation python in Miami, FL is $64,657.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,100.00 and $76,000.00 per year, depending on experience, location, and employer.

What is a physics simulation Python developer?

A Physics Simulation Python developer is a professional who uses the Python programming language to design, implement, and analyze simulations that model physical systems and phenomena. These simulations can range from simple particle motion to complex fluid dynamics or electromagnetic fields, and are widely used in research, engineering, gaming, and education. The developer typically utilizes scientific libraries such as NumPy, SciPy, and PyBullet, and may also work with visualization tools to present simulation results. Their work helps in understanding real-world physics problems, testing hypotheses, or creating realistic interactive environments.

What are the key skills and qualifications needed to thrive as a physics simulation Python developer?

To excel as a Physics Simulation Python Developer, you need a strong background in physics, mathematics, and proficiency in Python programming, often supported by a degree in physics, engineering, or computer science. Familiarity with simulation libraries (such as NumPy, SciPy, PyBullet, or SimPy), version control systems like Git, and experience with visualization tools are commonly required. Analytical thinking, problem-solving abilities, and effective collaboration are standout soft skills in this role. These skills enable the development of accurate, efficient simulations and foster productive teamwork in research or engineering projects.

What are some common challenges faced by professionals working in physics simulation with Python, and how can they be addressed?

Professionals in Physics Simulation with Python often encounter challenges such as optimizing simulation performance, ensuring numerical accuracy, and integrating complex libraries (e.g., NumPy, SciPy, PyBullet) into larger workflows. Addressing these issues typically involves using efficient coding practices, leveraging vectorized operations, and validating results with analytical solutions or experimental data. Collaboration with domain experts and regular code reviews can also help maintain code reliability and project scalability. Staying updated with the latest simulation frameworks and actively participating in open-source communities are excellent ways to overcome technical hurdles.

What is the difference between Physics Simulation Python vs Mechanical Engineer?

AspectPhysics Simulation PythonMechanical Engineer
Required CredentialsProgramming skills, knowledge of physics, often a degree in physics or computer scienceMechanical engineering degree, professional licensure in some regions
Work EnvironmentSoftware development, research labs, simulation environmentsDesign offices, manufacturing plants, R&D departments
Industry UsageSimulation software development, research, academiaProduct design, manufacturing, systems optimization

Physics Simulation Python focuses on developing and implementing physics-based simulations using Python programming, often in research or software development contexts. Mechanical Engineers apply engineering principles to design, analyze, and manufacture mechanical systems. While both roles require a strong understanding of physics, Physics Simulation Python emphasizes coding and simulation, whereas Mechanical Engineering involves practical design and application in physical systems.

What are popular job titles related to Physics Simulation Python jobs in Miami, FL?

For Physics Simulation Python jobs in Miami, FL, the most frequently searched job titles are:

What job categories do people searching Physics Simulation Python jobs in Miami, FL look for?

The top searched job categories for Physics Simulation Python jobs in Miami, FL are:

What cities near Miami, FL are hiring for Physics Simulation Python jobs?

Cities near Miami, FL with the most Physics Simulation Python job openings:

Physics Simulation Python jobs near you
Infographic showing various Physics Simulation Python job openings in Miami, FL as of August 2026, with employment types broken down into 1% Internship, 87% Full Time, 4% Part Time, and 8% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $64,657 per year, or $31.1 per hour.

Optomechanical Integration & Test Engineer (Miami, FL)

Miami, FL

Exowatt
See more jobs at Exowattexternal

$99K - $133K/yr

Full-time

Medical, Dental, Retirement

Re-posted 24 days ago

Job description

Exowatt is revolutionizing the energy landscape for the AI era with our groundbreaking P3 system that captures solar energy, stores it as heat, and generates electricity on demand. Founded in 2023 and backed by leading investors including Andreessen Horowitz, Sam Altman, and Felicis, we're committed to providing clean, modular, and scalable power that meets the rapidly growing demands of AI infrastructure. Our mission is to make sustainable renewable energy always available and almost free, enabling technological advancement while protecting our planet.
 
We are seeking an Optomechanical Integration & Test Engineer to join our optics team. The team owns the full design-to-commissioning lifecycle for our tracker hardware: precision optical elements and the structures that position them, solar tracking architectures, structural analysis under wind and gravity loading, and the instrumentation that turns prototypes into measured systems. This role owns that last part. The core problem: prove, with numbers you can defend, that precision optics on a large structure that moves all day, outdoors, under wind, gravity, and thermal swings, actually deliver the energy the models promise, and find out exactly why when they don't.

At its core, this is a measurement role for someone who likes to build. Nothing the team designs counts until it is measured, and you will own the infrastructure that produces those measurements: indoor optical benches, a high-flux test facility, and outdoor on-sun test stands. The full loop is yours: test plan to fixture design to instrumented stand to commissioning to data with error bars, learning from every campaign and turning the next test around in days, not months. You will spend most of your time hands-on at the bench, in the high-flux bay, and in the field. The work spans precision alignment, radiometry, thermal measurement, sensors and DAQ, and the Python and AI agents that run them. This is an AI-native team: agents already drive our simulation campaigns and babysit our long-running tests, and we expect you to engineer at that level from day one. A test stand you build is not finished until an agent can run it. Expect real ownership, a steep learning curve, and senior engineers who will review your work closely and push you to grow fast.

This position is based in Miami, FL. If selected, relocation to Miami, FL is required. Exowatt provides relocation assistance.
Key Responsibilities:
  • Own optical test stands end to end, from indoor characterization benches to the high-flux test facility to outdoor on-sun stands: concept, CAD, fixtures, instrumentation, commissioning, first light, and day-to-day operation
  • Design and run test campaigns from hypothesis to conclusion: write the test plan, build the setup, take the data, quantify the uncertainty, and present results that drive real design decisions
  • Characterize optical components and assemblies: alignment verification, focal and flux measurements, camera-based flux mapping, radiometry and thermal power measurement, reflectance and transmittance
  • Develop precision alignment procedures and tooling for optical assemblies on tracker platforms, and verify pointing and tracking accuracy in the field
  • Select, mount, wire, and calibrate instrumentation (radiometers and power sensors, thermocouples, cameras, tilt sensors, encoders, weather and irradiance instruments) and integrate everything into DAQ systems
  • Automate tests in Python: instrument control, data acquisition, analysis pipelines, and the plots and reports that make results legible to the whole team
  • Make the test infrastructure agent-ready: expose instruments, test sequencing, and data pipelines through clean scriptable interfaces so AI agents can configure a test, run it, watch it overnight, and flag anomalies, then use those agents to run campaigns that would otherwise wait on a human
  • Close the loop between simulation and hardware: compare measured optical performance against raytrace predictions and chase discrepancies to root cause, whether the flaw is in the hardware or in the measurement
  • Run environmental and durability testing on optical components (thermal cycling, weathering, soiling) and help build the reliability story for hardware that must survive decades outdoors
  • Own test safety around concentrated flux: hazard analyses, interlocks, PPE, and safe operating procedures for indoor high-flux testing and on-sun operations
  • Document test plans, procedures, results, and decisions on the team wiki; present and defend your own work in design reviews, growing into ownership of the team's test strategy over time
Qualifications:
  • BS or MS in Optical Engineering, Mechanical Engineering, Electrical Engineering, Aerospace Engineering, Physics, or a closely related discipline
  • 2+ years of hands-on laboratory, test, or integration experience with optical or precision hardware; graduate research and substantial internship work count
  • Strong fundamentals in math and physics: you reason from first principles, estimate before you compute, and check every result against known limits before you believe it; we probe this hard in interviews
  • Hands-on experience on an optical bench: mounting, aligning, and characterizing optics, and the care and cleanliness habits that precision components demand
  • Instrumentation fundamentals: sensor selection, signal conditioning, calibration, and DAQ integration
  • Python for test automation and data analysis: instrument control, numpy/pandas data reduction, publication-quality plots
  • Fluency with AI coding agents (Claude Code, Codex, or similar) as a daily engineering tool: you use them to write most of your code, and you own every line they produce, reviewed, tested, and understood; expect us to ask you to show how you work with AI the same way we ask about your bench skills
  • The instinct to make work agentic: you can decompose a workflow into steps an agent can execute, with clean interfaces, verifiable checkpoints, and guardrails, and you have the judgment to catch an agent when it is confidently wrong; engineers who can direct several agents at once will outrun those who type everything themselves, and we hire the former
  • Working knowledge of a parametric CAD tool for fixtures and test hardware; the team uses PTC Creo and SolidWorks
  • The discipline of good measurement: you control variables, calibrate before you trust, quantify uncertainty, and distrust your own data until the measurement itself is validated
  • A track record of building real test setups or hardware: research labs, internships, capstone projects, FSAE, solar car teams, robotics, or independent builds all count; bench experience matters more than coursework grades
  • The drive to own the full cycle yourself: take a question to a test plan, to a built stand, to trustworthy data, learn from the mistakes, and iterate quickly rather than handing steps off to others
  • Comfort with both bench and field work: precision optical alignment in the morning, commissioning an outdoor test stand in the Miami sun in the afternoon
  • Structured root-cause instincts when results look wrong: the first suspect is always the measurement, and you know how to clear or convict it
  • Strong written communication: your test reports should let the next engineer reproduce the measurement without asking you
  • The temperament to hold your ideas loosely: designs evolve weekly and priorities shift on real evidence; engineers who can let go and update move fastest
Preferred Qualifications:
  • Radiometry or photometry experience: power meters, flux mapping, camera-based flux measurement, IR thermography
  • Exposure to concentrating optics, heliostat or CPV testing, or high-flux measurement
  • Camera-based metrology and image processing: OpenCV or similar, converting images into calibrated measurements
  • Thermal measurement experience: calorimetry, heat flux sensors, flow-and-temperature-based power measurement
  • Design validation and reliability practices: DVP&R, accelerated aging, or environmental qualification against IEC/ASTM standards for solar hardware
  • Motion control experience: stages, encoders, motorized mounts, closed-loop pointing systems
  • Exposure to optical simulation (LightTools, Zemax, or another raytracer) and to comparing measurement against model
  • Statistics for test engineering: design of experiments, measurement system analysis, formal uncertainty budgets
  • Experience building agentic systems around real hardware or simulation: agents driving instruments or ray-trace models through tool interfaces (MCP or similar), running parameter sweeps overnight, and summarizing the results; or any project where you gave an AI real levers and made its output trustworthy
  • Machine shop skills and rapid prototyping: you can make the bracket you need instead of waiting for it
  • Interest in solar energy, heliostats, or large-scale renewable infrastructure
Additional Requirements:
  • Willingness to work extended hours and occasional weekends when test campaigns, commissioning windows, or program deadlines demand it
  • Ability to lift up to 25 lbs unassisted, and to work on ladders and lifts and around energized equipment and concentrated light with appropriate PPE
  • Ability to work outdoors in Miami heat for extended periods during field testing
  • Occasional travel to vendors, calibration labs, and field sites
What We Offer:
Competitive salary and equity options.
Comprehensive benefits package, including health, dental, and retirement plans.
A dynamic work environment that fosters creativity and innovation.
Opportunities for professional growth and development in a rapidly evolving industry.
Relocation assistance.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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