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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