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Tyba

Optimization Engineer

Reposted 2 Days Ago
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In-Office or Remote
7 Locations
160K-200K Annually
Mid level
In-Office or Remote
7 Locations
160K-200K Annually
Mid level
Lead end-to-end modeling initiatives to improve battery auto-bidding optimization. Implement and optimize dispatch models in code, improve solver performance and observability, debug production issues, and work cross-functionally to ensure interpretable, reliable decisions for customers.
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About Tyba

Tyba is a modeling platform for energy companies developing, financing, and operating renewable energy infrastructure. Energy companies rely on technical models daily to make crucial infrastructure decisions.

Our mission is to make cutting-edge models accessible to cross-functional teams so that companies can build and operate more renewable energy more profitably. We are backed by leading climate and generalist VCs and work with many of the industry’s most innovative energy companies.

The Role

We are looking for an Optimization Engineer to join our team and lead key modeling initiatives that deliver value to customers of our battery auto-bidding platform.

You will excel in this role if you’re passionate about clean energy, thrive in fast-paced environments, and have a strong sense of ownership. As an Optimization Engineer at Tyba, you will have the opportunity to contribute to a mission-critical product that synthesizes price forecasts and bid optimization algorithms to deliver market-beating returns for our customers.

You’ll work closely with cross-functional teams, going deep on the intricacies of power markets and their associated systems, turning customer needs into robust engineering solutions. This role primarily involves improving Tyba’s optimal battery dispatch model, with a focus on accurate and performant modeling approaches.

Tyba’s Product

Tyba has two main products for customers – Asset Operations and Project Simulation

Asset Operations: An Auto-bidding platform, powered by a proprietary neural network, that recommends and executes operating strategies based on industry-leading price forecasts and optimization methodology.

Project Simulation: A configurable simulation platform enabling developers to model realistic financial and physical outcomes based on location, market dynamics, and battery specifications.

As an Optimization Engineer, you’ll focus on improving the algorithms powering the Asset Operations auto-bidding platform.

Responsibilities

  • Leading new modeling initiatives end-to-end: This includes conducting relevant domain research, formulating mathematical models, and owning their implementations in code.

  • Performance engineering: Improve model formulations and investigate analytical decomposition approaches that can speed up time-to-solution in a live bidding system that must communicate with market systems on strict timelines.

  • Supporting decision interpretability and model introspection: Assist internal and external stakeholders with interpreting decisions from the battery dispatch model, building an intuitive understanding of relevant constraints and opportunity costs.

  • Enhancing and stewarding system reliability: This includes debugging production issues, ensuring that dispatch models handle anomalous third party and sensor data properly, and improving model observability, all in service of minimal system downtime.

Required Skills

  • 3+ years of energy systems optimization experience

  • Experience with Python and the CVXPY framework, especially deployed in a production context

  • Bachelor degree in Computer Science

  • Ability to work cross-functionally, synthesizing insights from non-technical team members and external parties to craft well-designed models

  • Passion for working in clean energy

Preferred Skills

  • Experience with robust optimization and/or stochastic optimization approaches for modeling risk and uncertainty

  • Experience with solver performance optimization for solving large problems efficiently

Tyba’s Technical Stack

Tyba’s machine learning and asset operations stack is written in Python and is deployed as a distributed system on the AWS cloud. Our optimization models are implemented in the CVXPY modeling framework.

Compensation and benefits

  • Salary: $160k-$200k

  • Benefits: Parental leave, medical benefits, unlimited PTO

  • Equity Options: Opportunity to own a stake in the company through an employee stock option plan.

  • Flexible Work Environment: Hybrid work model, remote work options, and team offsites.

Top Skills

AWS
Cvxpy
Python

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