Job VC
Senior Python Optimization Engineer - Gurobi / Unit Commitment
Technologies
Description
About The Role
We are looking for a
Senior Python Optimization Engineer / Gurobi Modeler
to support a Python-based
Unit Commitment
model that uses
Gurobi as a MILP solver
.
This is expected to be a
long-term, part-time engagement
with regular overlap with
US Eastern Time
. The role will help maintain, troubleshoot, and extend the existing model as it becomes part of a standard customer offering. Workload may vary over time, with occasional ramp-up during customer implementations and lighter ongoing support between projects.
The ideal candidate combines strong Python engineering, practical MILP modeling experience, and hands-on Gurobi knowledge. Experience in power systems, energy markets, or Unit Commitment is strongly preferred.
Key Responsibilities
Maintain and enhance an existing Python-based Unit Commitment optimization model.
Troubleshoot model behavior, infeasibility issues, solver performance, and customer-specific cases.
Extend the model with new constraints, business rules, objective terms, or configuration options.
Provide ongoing part-time support for issues that arise between implementation projects.
Improve model maintainability, structure, documentation, and repeatability.
Work with client-side product teams and engineering stakeholders to clarify requirements and validate results.
Document model assumptions, formulation logic, known limitations, changes, and troubleshooting steps.
Technical Requirements
Required:
Strong Python development experience.
Hands-on experience with Gurobi.
Practical experience building, maintaining, or extending MILP optimization models.
Ability to debug optimization models, including infeasibility, constraint behavior, and solver performance issues.
Experience working with existing codebases and improving model maintainability.
Ability to understand mathematical formulations and translate them into production-quality Python code.
Strong analytical and problem-solving skills.
Good written and spoken English communication.
Reliable availability for a part-time engagement.
Regular working-hours overlap with US Eastern Time.
Nice To Have:
Experience with Unit Commitment models.
Experience in power systems, electricity markets, energy optimization, or production cost modeling.
Familiarity with economic dispatch, reserves, ramping constraints, startup/shutdown logic, min up/down times, renewables, storage, or transmission constraints.
Experience with pandas, NumPy, or similar Python optimization/data libraries.
Experience tuning Gurobi models for performance.
Experience productizing analytical or optimization models for repeat customer use.
Experience supporting customer implementations or production troubleshooting.
Ability to explain model behavior and tradeoffs to both technical and non-technical stakeholders.
We are looking for a
Senior Python Optimization Engineer / Gurobi Modeler
to support a Python-based
Unit Commitment
model that uses
Gurobi as a MILP solver
.
This is expected to be a
long-term, part-time engagement
with regular overlap with
US Eastern Time
. The role will help maintain, troubleshoot, and extend the existing model as it becomes part of a standard customer offering. Workload may vary over time, with occasional ramp-up during customer implementations and lighter ongoing support between projects.
The ideal candidate combines strong Python engineering, practical MILP modeling experience, and hands-on Gurobi knowledge. Experience in power systems, energy markets, or Unit Commitment is strongly preferred.
Key Responsibilities
Maintain and enhance an existing Python-based Unit Commitment optimization model.
Troubleshoot model behavior, infeasibility issues, solver performance, and customer-specific cases.
Extend the model with new constraints, business rules, objective terms, or configuration options.
Provide ongoing part-time support for issues that arise between implementation projects.
Improve model maintainability, structure, documentation, and repeatability.
Work with client-side product teams and engineering stakeholders to clarify requirements and validate results.
Document model assumptions, formulation logic, known limitations, changes, and troubleshooting steps.
Technical Requirements
Required:
Strong Python development experience.
Hands-on experience with Gurobi.
Practical experience building, maintaining, or extending MILP optimization models.
Ability to debug optimization models, including infeasibility, constraint behavior, and solver performance issues.
Experience working with existing codebases and improving model maintainability.
Ability to understand mathematical formulations and translate them into production-quality Python code.
Strong analytical and problem-solving skills.
Good written and spoken English communication.
Reliable availability for a part-time engagement.
Regular working-hours overlap with US Eastern Time.
Nice To Have:
Experience with Unit Commitment models.
Experience in power systems, electricity markets, energy optimization, or production cost modeling.
Familiarity with economic dispatch, reserves, ramping constraints, startup/shutdown logic, min up/down times, renewables, storage, or transmission constraints.
Experience with pandas, NumPy, or similar Python optimization/data libraries.
Experience tuning Gurobi models for performance.
Experience productizing analytical or optimization models for repeat customer use.
Experience supporting customer implementations or production troubleshooting.
Ability to explain model behavior and tradeoffs to both technical and non-technical stakeholders.