We’re on a mission to improve the reliability, transparency, and efficiency of our energy systems, fostering a future with sustainable and abundant energy. To accomplish our aims, we’re using machine learning and convex optimization methods to build the financial rails of our future energy systems that will accelerate the deployment of clean energy resources.
We envision energy systems that are efficient, autonomous, resilient, and powered by 100% renewable energy.
Our founders (ex-Apple, Bluevine; ex-Affirm, Square, Google) are Stanford alumni with experience with complex systems, machine learning, and structured finance. Our world-class investors, Maverick Ventures and Caffeinated Capital, are aligned to our policy objectives and platform vision.
Comity is looking for a Senior Machine Learning Engineer to help develop our energy pricing models and facilitate their deployment in market-leading power contract origination strategies.
You’ll work closely with our Quantitative Researchers to design and deploy models and optimization algorithms for participating in wholesale power markets, and ensure that they can scale to new markets and greater volume. You will help develop our data infrastructure and research platform, which give our researchers streamlined access to relevant data sources and powerful computing resources, as well as the confidence that their research will translate into real-world results. As an early hire in this role, you will have broad impact and ownership over our platform and framework design, research agenda, technology choices, and team culture.
You have 5+ years of professional software engineering experience and 3+ years of experience developing production machine learning (or other predictive modeling) systems in an industry setting.
You have experience leading and mentoring software engineers, ML engineers, or data scientists.
You have a solid grasp of machine learning fundamentals and can read research results to understand operational requirements and assumptions.
You are experienced and comfortable with the workflow to research and develop machine learning models and data mining algorithms, working with distributed computing resources and structured, graph, spatial, and time series data.
You are a lifelong learner and empathetic teacher. We’re committed to the growth and development of our teammates. We work towards a shared understanding by listening with intent and holding open discussions because we know that's how we'll deliver quality results.
We believe strong foundations are more important than specific technical knowledge, but experience with any part of our data stack (Python, SQL, PyTorch, CatBoost) is a plus.
We’re headquartered in New York City, with a flexible approach to remote work and work from home.