Machine Learning Engineer

Summary

Join Equilibrium Energy, a Series B clean energy startup, as an ML Engineer and contribute to revolutionizing the clean energy transition. You will be part of the Science Platform team, developing and maintaining scalable ML pipelines for forecasting and optimization models. Collaborate with data scientists, integrate with data infrastructure, and implement automated testing and monitoring. Partner with product and customer delivery teams to enable external customers to utilize the platform. Stay current with advancements in ML engineering and integrate best practices. This role requires proficiency in Python, experience with various tools and technologies, and strong communication skills.

Requirements

• A commitment to clean energy and combating climate change
• Proficiency in Python software development
• Familiarity with automated build, deployment, and orchestration tools such as CI/CD, Pants, Docker, Metaflow, and Kubernetes
• Strong understanding of data pipelines, ETL, and data infrastructure
• Experience with observability tooling like Grafana, Honeycomb, and Prometheus
• Experience with common machine learning algorithms and libraries (xgboost, sklearn, pytorch, pandas, polars, pandera)
• Prior experience in operationalizing machine learning workflows
• Agility in working with cross-functional teams and adapting to new work methodologies
• Familiarity with agile practices, or a willingness to learn
• Strong communication skills for collaborating within a remote-first team that works internationally across timezones

Responsibilities

• Develop and maintain scalable ML pipelines, used to support forecasting and optimization models
• Design frameworks that support model experimentation, hyperparameter tuning, training, and deployment
• Collaborate closely with data scientists to understand new model requirements and together implement solutions that are robust, validated, and scalable
• Integrate with data and compute infrastructure to optimize resource utilization and performance
• Implement automated testing and monitoring for ML models in production
• Partner with our Product and Customer Delivery teams to enable external customers to perform similar tasks to our internal scientists, with minimal code divergence and following security best practices
• Stay up-to-date with the latest advancements in ML engineering and integrate best practices into the platform

Preferred Qualifications

• An advanced degree in computer science or machine learning
• Experience in time series forecasting
• Experience building tools that support data scientists
• Experience with Databricks, Spark, and dbt
• Background in the energy and power systems sector

Benefits

• 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