Optimization Software Engineer

Certus Sales Recruitment; Austin (TX); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Competitive base salary

Generous PTO

Professional development

Health, dental, and vision coverage

Job summary

Certus Sales Recruitment seeks an Optimization Software Engineer in Austin, TX to build and deploy optimization and forecasting models for a trading/asset management platform. Develop in Python and deploy on cloud infrastructure to enable real-time operations.

The role emphasizes end-to-end model development, optimization techniques (MILP/CVXPY), and cross‑team collaboration to deliver measurable impact in fast-moving power markets.

Qualifications

• Hands-on optimization with MILP, CVXPY for real-time MPC.

Responsibilities

• End-to-End Model Development
• Optimization for Physical Systems
• Deployment & Productionization
• Simulation & Back Testing
• Cross‑Team Collaboration

Skills

Applied Optimization Expertise

Full-Stack Software Experience

Commercial Focus

Software Development Practices

Tools

MILP

CVXPY

Pandas

NumPy

CI/CD

Cloud deployment

Job description

Optimization Software Engineer - Austin, TX - Competitive Salary + Excellent Benefits

Our client is seeking a Senior Data Scientist/Optimization Software Engineer to build and deploy optimization and forecasting models that power a trading and asset management platform. This includes linear, mixed‑integer, nonlinear, and stochastic optimization for bidding, congestion management, and real‑time model predictive control of battery storage under uncertainty, along with scalable back‑testing and simulation frameworks to evaluate and refine performance. You will work end‑to‑end, from developing models in Python to deploying them on cloud infrastructure, ensuring algorithms deliver real impact in fast‑moving power markets.

The ideal candidate will bring expertise in data science, power markets, and scalable model deployment.

Responsibilities

• End-to-End Model Development - Take projects from research through production, building robust, scalable optimization and forecasting solutions.
• Optimization for Physical Systems - Apply linear, mixed‑integer, nonlinear, and stochastic optimization techniques to real‑time model predictive control of systems such as battery storage (BESS), robotics, and industrial machinery.
• Deployment & Productionization - Develop in Python and deploy on cloud infrastructure, ensuring performance and reliability in fast‑moving, real‑world environments.
• Simulation & Back Testing - Build frameworks to evaluate and refine algorithmic performance at scale.
• Cross‑Team Collaboration - Partner with trading, data science, and software engineering teams to ensure solutions deliver measurable impact.

Requirements

• Applied Optimization Expertise - Hands‑on experience with tools such as MILP, CVXPY, or equivalent for real‑time model predictive control of physical systems.
• Full-Stack Software Experience - Strong Python skills with familiarity across the broader data and software ecosystem (Pandas, NumPy, CI/CD, cloud deployment).
• Commercial Focus - Proven applied experience in a commercial or industrial context, with preference over purely academic backgrounds.
• Software Development Practices - Solid grounding in version control, testing, and managing dev/test/production workflows.
• Location Requirement - Based in Austin, TX. Remote candidates will be considered for Hybrid role.

Benefits

• Competitive base salary
• Generous PTO
• Professional development
• Comprehensive medical, dental, and vision coverage
• Flexible hybrid working (3 days WFH per week)