Hiring Simulation Engineers: The Complete Guide

# Simulation Engineer

**Location:** San Francisco, CA (Hybrid) · **Employment Type:** Full-time · **Level:** Mid-Senior

## About [Company]

[Company] is building autonomous delivery robots that navigate city sidewalks, delivering packages in 15 cities. Our simulation platform is critical for testing robot behavior at scale—we run 10 million simulated miles weekly to find issues before they happen in the real world.

Simulation is how we iterate fast while staying safe. Every new perception model, planning algorithm, or behavior change gets validated against millions of scenarios before touching a real robot.

**Why join [Company]?**

- Work on simulation at scale—10M simulated miles weekly
- Enable rapid autonomy development with high-fidelity testing
- Solve hard problems (physics, sensors, scenario generation)
- Join a 12-person simulation team within a 200-person engineering org
- Series C company backed by top robotics investors
- Competitive compensation with meaningful equity

## The Role

We're looking for a Simulation Engineer to help us build world-class simulation for robotics testing and validation. You'll work on physics simulation, sensor modeling, scenario generation, and the infrastructure that enables testing at massive scale.

Good simulation is the difference between fast iteration and slow, expensive real-world testing. Your work enables the perception team to train models on synthetic data, the planning team to test edge cases, and the whole company to ship with confidence.

The ideal candidate has experience building simulation systems and understands the gap between simulation and reality. You know that perfect physics isn't the goal—useful simulation that catches real bugs is.

## What You'll Work On

### First 30 Days
- Onboard to our simulation stack, scenario library, and validation systems
- Understand how simulation integrates with perception, planning, and testing
- Ship your first improvement (physics tweak, sensor model, or scenario)

### First 90 Days
- Own a simulation system component (physics, sensors, or scenario generation)
- Contribute to simulation fidelity or scale improvements
- Build or improve synthetic data pipelines
- Collaborate with perception and planning on their simulation needs

### First Year
- Lead simulation initiatives that accelerate autonomy development
- Architect improvements to our simulation platform
- Develop new capabilities (weather, crowds, rare events)
- Mentor teammates on simulation engineering best practices

## Objectives of This Role

- Improve simulation-to-reality correlation for key metrics
- Increase simulation scale to 2x current capacity
- Expand scenario coverage for edge cases and rare events
- Build synthetic data pipelines that accelerate ML training
- Reduce time-to-simulation for new features

## Responsibilities

**Physics Simulation (40%)**
- Build and improve robot physics simulation (dynamics, kinematics)
- Model environment physics (surfaces, collisions, weather effects)
- Validate simulation against real-world robot behavior
- Optimize physics for performance at scale
- Handle edge cases (stairs, curbs, unusual surfaces)

**Sensor Simulation (35%)**
- Develop sensor simulation (cameras, LiDAR, IMU, GPS)
- Model sensor noise and failure modes
- Generate synthetic training data for perception models
- Validate sensor models against real sensor data
- Build domain randomization for robust training

**Scenario & Infrastructure (25%)**
- Create scenario generation systems for testing
- Build procedural content generation for variety
- Optimize simulation infrastructure for parallel execution
- Design scenario coverage and test prioritization
- Collaborate with QA on simulation-based testing

## Required Skills and Qualifications

**Technical Skills**
- 5+ years of software engineering experience
- 2+ years in simulation, robotics, or game development
- Strong physics simulation experience (rigid body, kinematics)
- Game engine or simulation platform knowledge (Unity, Unreal, Isaac Sim)
- Performance optimization experience for real-time or batch simulation
- Proficiency in C++ and/or Python

**Simulation Knowledge**
- Understanding of numerical methods and physics integration
- Experience with sensor modeling or synthetic data generation
- Familiarity with simulation validation methodologies

**Soft Skills**
- Collaboration with perception, planning, and testing teams
- Analytical approach to simulation-reality gap analysis
- Clear communication about simulation limitations

## Preferred Skills and Qualifications

- Robotics simulation experience (Isaac Sim, Gazebo, CARLA)
- Autonomous vehicle or mobile robot experience
- Camera and LiDAR sensor modeling experience
- ML training data generation experience
- Background in physics or mechanical engineering
- Game engine development experience

## Tech Stack

**Simulation:** NVIDIA Isaac Sim, custom physics, Unity for visualization

**Backend:** C++, Python, custom scenario generation

**ML Integration:** PyTorch, synthetic data pipelines

**Infrastructure:** AWS (EC2 with GPUs), Kubernetes for batch jobs

**Rendering:** GPU rendering for sensor simulation, ray tracing

## Compensation and Benefits

**Salary:** $155,000 - $210,000 (based on experience)

**Equity:** 0.05% - 0.15% (4-year vest, 1-year cliff)

**Benefits:**

*Health & Wellness*
- Medical, dental, and vision insurance (100% covered)
- $100/month wellness stipend
- Mental health support through Modern Health

*Time Off*
- Unlimited PTO with 15-day minimum encouraged
- 11 paid company holidays
- 16 weeks paid parental leave

*Professional Development*
- $3,000 annual learning budget
- Conference attendance (GTC, ROSCon, CoRL)
- Internal robotics tech talks

*Financial*
- 401(k) with 4% company match
- Equity refresh grants annually

*Workspace*
- $1,500 home office setup allowance
- Hybrid work (2-3 days in SF office)
- Access to robot test facilities

## Engineering Culture

**How we work:**
- Simulation enables safe iteration—we test extensively before real-world
- Data-driven validation—simulation must correlate with reality
- Close collaboration with perception and planning teams
- Regular simulation-reality comparison studies
- Blameless post-mortems when simulation misses issues

**What we value:**
- Practical simulation that catches real bugs
- Balance between fidelity and performance
- Understanding simulation's limitations
- Enabling other teams to move fast safely
- Continuous improvement of simulation-reality correlation

## Interview Process

Our interview process typically takes 2 weeks.

- **Step 1: Recruiter Screen** (30 min)
  Background discussion and role overview.

- **Step 2: Technical Screen** (60 min)
  Simulation and systems fundamentals.

- **Step 3: Simulation Deep Dive** (90 min)
  Technical discussion about physics, sensors, and your simulation experience.

- **Step 4: System Design** (75 min)
  Design a simulation system component (physics, sensor model, or scenario generation).

- **Step 5: Coding Exercise** (75 min)
  Implementation exercise related to simulation.

- **Step 6: Team Interviews** (2 x 30 min)
  Meet potential teammates from simulation and autonomy teams.

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*[Company] is an equal opportunity employer.*