What we are looking for Equilibrium was founded with a vision for building a company where data-centric decision-making drives our operations. Our reliance on closed-loop, ML-infused, autonomous workflow decision-making makes simulating and interpreting market performance core to our success as a company. We are looking for a research software engineer who will be responsible for building software tools that allow sophisticated simulation of the physical and economic characteristics of utility-scale battery operations.
What you will do Design, develop, and maintain features for a utility-scale battery simulation platform
Create a platform for visualizing and inspecting battery simulation results that enables actionable insights from performance and risk metrics Serve as a subject matter expert on simulation run mechanics and energy market logic Build tools for the ingestion and processing of time series data from various internal and external sources Assist in product development strategy, design, planning, and productivity.
Contribute your unique technical, user, and market knowledge to product strategy Contribute to product roadmapping, resource planning, and sprint management Contribute to product development productivity improvements, including best practices, technical documentation, code reviews, and automation/utility/abstraction packages. Serve as a member of our technical team across both engineering and research.
Collaborate asynchronously with engineers, researchers, and product managers across time zones to design, build, and ship code. Contribute to technical strategy and planning across the company. The minimum qualifications you'll need 4+ years of production software engineering experience (Python, C++, Julia, or other applicable languages) Experience working across the software/research boundary, preferably in one of the following domains: machine learning, optimization, quantitative trading, power systems research Familiarity with software development best practices, including version control, code reviews, CI/CD, and testing Experience analyzing computational results with tooling such as Jupyter notebooks and matplotlib or equivalent Ability to proactively communicate and work cross-functionally to define and implement solutions in a complex technical environment BA/BS/Master's degree in a quantitative discipline (e.g. Computer Science, Mathematics, Mechanical Engineering) or equivalent practical experience Nice to have additional skills Domain experience in simulation of real-world assets (physical batteries, autonomous vehicles, etc.) Working knowledge of modern cloud infrastructure and containerization tools (e.g. Docker, Kubernetes, AWS/GCP/Azure) Experience with SQL-based databases (e.g. PostgreSQL) as well as tools and frameworks for working with databases programmatically (e.g. ORMs, JDBC, etc.) Experience with speed/memory tradeoffs operating over large-scale datasets Experience with optimization techniques, modeling packages, and solvers
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