Research Engineer (Physics Simulation)
Who You Are
Phaidra is looking for a curious and pragmatic Research Engineer with a passion for physics and a knack for writing robust code. You will work within our research team to develop advanced physics-based simulators, with a particular focus on thermodynamics and fluid mechanics. These simulators are key to enabling intelligent control systems that optimize performance in industrial environments.
You thrive at the intersection of science and engineering—able to translate complex physical systems into computational models and build tools that power cutting-edge AI systems.
We are seeking a team member located within one of the following areas: UK (preferred), USA, or Canada.
In the United States, we accept applicants located in the following states: California, Colorado, Connecticut, Georgia, Florida, Indiana, Maryland, Minnesota, Missouri, Nebraska, New York, North Carolina, Pennsylvania, South Carolina, Tennessee, Texas, Virginia, Washington.
In Canada, we accept applicants located in the following provinces: Ontario, British Columbia, and Alberta.
Responsibilities
As a Research Engineer working on Physics Simulators, you will:
Design and implement physics-based simulation models for thermodynamic and fluid systems.
Translate governing equations and first-principles models into performant numerical code.
Collaborate with AI researchers to integrate simulators with reinforcement learning agents and optimization pipelines.
Validate simulators against real-world data and iterate to improve fidelity and stability.
Be a power user and contributor to Phaidra’s simulation and AI platform, enabling scalable, reusable experimentation.
Document and communicate technical ideas clearly across teams.
Key Qualifications
1+ years of experience in research or applied engineering.
Bachelor's or Master’s degree in Mechanical Engineering, Chemical Engineering, Applied Physics, or related field.
Strong understanding of thermodynamics and fluid mechanics and HVAC systems.
Experience building simulation tools using numerical methods (e.g., finite difference, ODE/PDE solvers).
Proficiency in Python and scientific computing libraries (e.g., NumPy, SciPy, SymPy, pandas).
Familiarity with simulation or modeling frameworks (e.g., Modelica, OpenFOAM, COMSOL, EnergyPlus, or custom-built tools).
Comfortable reading academic papers and implementing physics models from scratch.
Share our company values: Collaboration, Transparency, Operational Excellence, Ownership, and Empathy.
Preferred Skills & Experience
Knowledge of controls and optimization techniques (e.g., PID, MPC, or RL).
Experience integrating simulation tools with machine learning workflows.
Experience working with large-scale systems or infrastructure in energy, HVAC, or industrial automation.
Familiarity with modern software engineering practices (Docker, Git, CI/CD).
Our Stack
Python, NumPy, SciPy, pandas, SymPy
PyTorch, Ray, scikit-learn
Docker, Kubernetes, Terraform
GCP
Onboarding
In your first 30 days...
You’ll onboard into Phaidra’s product and research ecosystem.
You’ll study our current modeling work, simulation tools, and customer use cases.
You’ll set up your environment and begin replicating existing physics models in code
By your first 60 days...
You’ll begin contributing to one or more simulator development projects.
You’ll work closely with researchers to define simulation specs and performance metrics.
You’ll review field data to inform model accuracy and validation criteria.
By your first 90 days...
You’ll be actively developing, validating, and improving simulation modules.
You’ll have results from early experiments and have contributed code to core libraries.
You’ll be shaping the direction of simulator design and pushing the envelope of physics + AI integration
General Interview Process
All of our interviews are held via Google Meet, and an active camera connection is required.
Meeting with People Operations team member (30 minutes)
Initial Meeting with Hiring Manager (30 minutes)
Meeting with a member of the Machine Learning Application Engineering team (60 minutes)
Deep Dive with Hiring Manager (60 minutes)
Culture fit interview with Phaidra’s co-founders (30 minutes)
Base Salary
United States Residents
San Francisco/New York Metro: 112,000 USD - 168,000 USD
Other cities: 92,800 USD - 156,000 USD
Canada Residents
Toronto/Vancouver: 106,400 CAD - 170,400 CAD
Other cities: 83,200 CAD - 136,800 CAD
UK Residents
76,000 GBP - 114,000 GBP
This position will also include equity.
These are best faith estimates of the base salary range for this position. Multiple factors such as experience, education, level, and location are taken into account when determining compensation.
About the job
Apply for this position
Research Engineer (Physics Simulation)
Who You Are
Phaidra is looking for a curious and pragmatic Research Engineer with a passion for physics and a knack for writing robust code. You will work within our research team to develop advanced physics-based simulators, with a particular focus on thermodynamics and fluid mechanics. These simulators are key to enabling intelligent control systems that optimize performance in industrial environments.
You thrive at the intersection of science and engineering—able to translate complex physical systems into computational models and build tools that power cutting-edge AI systems.
We are seeking a team member located within one of the following areas: UK (preferred), USA, or Canada.
In the United States, we accept applicants located in the following states: California, Colorado, Connecticut, Georgia, Florida, Indiana, Maryland, Minnesota, Missouri, Nebraska, New York, North Carolina, Pennsylvania, South Carolina, Tennessee, Texas, Virginia, Washington.
In Canada, we accept applicants located in the following provinces: Ontario, British Columbia, and Alberta.
Responsibilities
As a Research Engineer working on Physics Simulators, you will:
Design and implement physics-based simulation models for thermodynamic and fluid systems.
Translate governing equations and first-principles models into performant numerical code.
Collaborate with AI researchers to integrate simulators with reinforcement learning agents and optimization pipelines.
Validate simulators against real-world data and iterate to improve fidelity and stability.
Be a power user and contributor to Phaidra’s simulation and AI platform, enabling scalable, reusable experimentation.
Document and communicate technical ideas clearly across teams.
Key Qualifications
1+ years of experience in research or applied engineering.
Bachelor's or Master’s degree in Mechanical Engineering, Chemical Engineering, Applied Physics, or related field.
Strong understanding of thermodynamics and fluid mechanics and HVAC systems.
Experience building simulation tools using numerical methods (e.g., finite difference, ODE/PDE solvers).
Proficiency in Python and scientific computing libraries (e.g., NumPy, SciPy, SymPy, pandas).
Familiarity with simulation or modeling frameworks (e.g., Modelica, OpenFOAM, COMSOL, EnergyPlus, or custom-built tools).
Comfortable reading academic papers and implementing physics models from scratch.
Share our company values: Collaboration, Transparency, Operational Excellence, Ownership, and Empathy.
Preferred Skills & Experience
Knowledge of controls and optimization techniques (e.g., PID, MPC, or RL).
Experience integrating simulation tools with machine learning workflows.
Experience working with large-scale systems or infrastructure in energy, HVAC, or industrial automation.
Familiarity with modern software engineering practices (Docker, Git, CI/CD).
Our Stack
Python, NumPy, SciPy, pandas, SymPy
PyTorch, Ray, scikit-learn
Docker, Kubernetes, Terraform
GCP
Onboarding
In your first 30 days...
You’ll onboard into Phaidra’s product and research ecosystem.
You’ll study our current modeling work, simulation tools, and customer use cases.
You’ll set up your environment and begin replicating existing physics models in code
By your first 60 days...
You’ll begin contributing to one or more simulator development projects.
You’ll work closely with researchers to define simulation specs and performance metrics.
You’ll review field data to inform model accuracy and validation criteria.
By your first 90 days...
You’ll be actively developing, validating, and improving simulation modules.
You’ll have results from early experiments and have contributed code to core libraries.
You’ll be shaping the direction of simulator design and pushing the envelope of physics + AI integration
General Interview Process
All of our interviews are held via Google Meet, and an active camera connection is required.
Meeting with People Operations team member (30 minutes)
Initial Meeting with Hiring Manager (30 minutes)
Meeting with a member of the Machine Learning Application Engineering team (60 minutes)
Deep Dive with Hiring Manager (60 minutes)
Culture fit interview with Phaidra’s co-founders (30 minutes)
Base Salary
United States Residents
San Francisco/New York Metro: 112,000 USD - 168,000 USD
Other cities: 92,800 USD - 156,000 USD
Canada Residents
Toronto/Vancouver: 106,400 CAD - 170,400 CAD
Other cities: 83,200 CAD - 136,800 CAD
UK Residents
76,000 GBP - 114,000 GBP
This position will also include equity.
These are best faith estimates of the base salary range for this position. Multiple factors such as experience, education, level, and location are taken into account when determining compensation.