Machine Learning Scientist (m/w/d)

Equilibrium Energy is revolutionizing the clean energy transition by developing innovative grid-scale energy storage solutions. Our technology and market platform helps utilities, independent power producers, and commercial customers optimize their renewable energy assets, improve grid reliability, and accelerate decarbonization. As a fast-growing climate tech company, we're building infrastructure that will shape the future of energy markets and enable a sustainable energy economy.

Equilibrium Energy is a well-funded, Series B clean energy startup backed by some of the most prominent institutional investors in climate. New colleagues will share our vision that a next-generation energy company must be built from the ground up on deep industry expertise combined with an unwavering commitment to modern digital approaches. We’re looking for collaborative, talented, passionate and resourceful folks to join our team and help us lay the foundation for our important mission and ambitious plan.

What we are looking for

Equilibrium was founded with a vision for building a company where innovation, collaboration, machine learning, and data science power all aspects of our algorithmic decision-making. We are looking for staff / sr staff machine learning scientists to accelerate the design and delivery of our machine learning models, probabilistic forecasts, and insights dashboards, while helping to shape the science-driven products & processes that will drive the future success of our company.

As a key member of our sciences group, you will play an active role in a) cultivating our culture of experimentation, insights discovery, and incremental delivery, b) facilitating research into state of the art machine learning techniques, c) helping to identify, recruit, train, and mentor members of our growing team of exceptional scientists, and d) partnering with our engineers, product managers, analysts, and commercial team to influence the near to medium term product roadmap.

What you will do

• Use research insights to shape product direction: Influence product and engineering roadmaps through presentation of research insights, experimental results, and model performance metrics, in order to evolve organizational direction. Initiate and lead cross-functional engagements to surface, prioritize, formulate, and structure complex and ambiguous challenges where advanced novel deep learning research can have outsized company impact.
• Formulate and apply novel machine learning solutions to the energy domain: Tackle complex deep learning & machine learning problems by researching published academic literature, surveying industry techniques & intuition, and executing hands-on experimental testing & modeling. Drive the design, specification, development, and production deployment of our suite of novel deep learning & machine learning solutions. Lead short to medium term research projects that advance the state-of-the-art in deep learning as applied to energy asset management and financial trading.
• Performance evaluation: Define and evaluate a suite of success metrics across our portfolio of candidate and deployed machine learning models in order to understand operational characteristics, diagnose sources of under-performance, and identify opportunities for further research & improvement.

The minimum qualifications you’ll need

• Passion for clean energy and fighting climate change
• An advanced degree in computer science, data science, machine learning, artificial intelligence, operations research, engineering, or related quantitative discipline
• 4+ years experience in data science, research science, machine learning, or similar role, applying and adapting deep learning, graph neural networks, or reinforcement learning techniques to time series regression & forecasting problems
• 2+ years experience in the electricity & energy domain (e.g. electricity price forecasting, congestion prediction etc)
• 3+ years experience with python and the supporting computational science tool suite (e.g. numpy, scipy, pandas, scikit-learn, tensorflow, etc.)
• Experience developing, releasing, and tracking performance of ML models in production
• Experience communicating mathematical concepts, analytical results, and data-driven insights to both technical and non-technical audiences
• A collaboration-first mentality, with a willingness to teach as well as learn from others

Nice to have additional skills

• Experience designing and building novel statistical models on time series data, including characterizing probabilistic outcome uncertainty
• Experience with dimensionality reduction, component decomposition, or embedding space analysis & visualization techniques (e.g. UMAP, T-SNE, Autoencoder)
• Experience with model explainability methods (e.g. SHAP)
• Experience with database technologies and sql
• Experience with probability, hypothesis testing, and uncertainty quantification
• Experience with optimization techniques (e.g. stochastic optimization, robust optimization)
• Experience with data visualization and dashboarding technologies (e.g. plot.ly Dash, Streamlit)
• Experience leading and mentoring a team of scientists
• Demonstrated track record of academic paper or social media publication

Not sure this is the right role for you?

We are a high growth company with accelerating hiring needs so there’s a great chance we’ll be able to create a custom role for you, now or in the future. All roles, titles and compensation packages are tailored to the applicant, so apply anyways and tell us in your cover letter about your dream role.

What we offer

Equilibrium is composed of deeply knowledgeable industry experts across all our functions, with decades of experience in energy-specific commercial structuring, power systems engineering, machine learning, computational research, operations research, distributed and compute-intensive infrastructure, and modern software & ML engineering. Our experience in the space means we’ve previously built versions of nearly every technical component of our platform. We are now designing them better, and combining them in a holistic and novel way, to achieve global scale and climate impact. We pride ourselves on our deeply empathetic & collaborative culture, honest and direct but respectful communication, and our balanced, flexible, and remote-first work environment.

Employee benefits include:

• Competitive base salary and a comprehensive medical, dental, vision, and 401k package
• Opportunity to own a significant piece of the company via a meaningful equity grant
• Unlimited vacation and flexible work schedule
• Ability to work remotely from anywhere in the United States, Canada & Europe, or join one of our regional hubs in Boston, SF Bay Area, or London
• Accelerated professional growth and development opportunities through direct collaboration and mentorship from leading industry expert colleagues across energy and tech

Equilibrium Energy is a diverse and inclusive, equal opportunity employer that does not discriminate on the basis of race, gender, nationality, sexual orientation, veteran status, disability, age, or other legally protected status.