Energy Engineer

The world today is filled with static, monolithic infrastructure. Factories, power plants, buildings, etc. operate the same they've operated for decades — because the controls programming is hard-coded. Thousands of lines of rules and heuristics that define how the machines interact with each other. The result of all this hard-coding is that facilities are frozen in time, unable to adapt to their environment while their performance slowly degrades.

Phaidra creates AI-powered control systems for the industrial sector, enabling industrial facilities to automatically learn and improve over time. Specifically:

• We use reinforcement learning algorithms to provide this intelligence, converting raw sensor data into high-value actions and decisions.
• We focus on industrial applications, which tend to be well-sensorized with measurable KPIs — perfect for reinforcement learning.
• We enable domain experts (our users) to configure the AI control systems (i.e. agents) without writing code. They define what they want their AI agents to do, and we do it for them.

Our team has a track record of applying AI to some of the toughest problems. From achieving superhuman performance with Deep Mind's Alpha Go, to reducing the energy required to cool Google's Data Centers by 40%, we deeply understand AI and how to apply it in production for massive impact.

Phaidra is based in the USA but 100% remote; we do not have a physical office. We hire employees internationally with the help of our partner, OysterHR. Our team is currently located throughout the USA, Canada, UK, Norway, Italy, Spain, Portugal, and India.

Please only apply to one opening. If you are a better fit for another opening, our team will move your application. Candidates who apply to multiple openings will not be considered.

Who You Are

The responsibility of the Energy Engineer is to validate energy savings for our customer sites and demonstrate findings through data analytics. This role will leverage technical skills to determine root cause analysis of previous performance and provide insights for system improvements.

Responsibilities

• Determine best fit baseline data and the savings methodology for a customer.
• Work closely with the data scientist team to generate meaningful and compelling charts, graphs, and data visualizations that portray the performance of the system.
• Coordinate with the Customer Success team to analyze platform availability status (uptime).
• Monitor projects for performance during the evaluation period. Protect Phaidra’s liability.
• Analyze customer data for opportunities for improvement and optimization.
• Collaborate with other teams on methods to improve system performance and share knowledge on your data findings.
• Communicate performance across all key metrics to our customers on a regular cadence.
• Present results to different levels of customer stakeholders in a clear and effective manner. Answer additional questions in a concise and thoughtful manner.
• Develop and present annual savings reports with supporting analytics examples and insights.
• Ensure on time delivery of reports in order to uphold excellent customer service and support. Coordinate with the customer to determine the best cadence for results reviews.
• Identify and construct tools and documentation to automate monthly savings results.
• Build company standards and playbooks around M&V and how it applies to the world of artificial intelligence.
• Maintain clear and concise documentation of methodologies and insights from each of the customer sites.

We are seeking a team member located within one of the following areas: USA/Canada

Key Qualifications

• 5+ years experience in Measurement & Verification, Energy Engineering, Optimization Engineering, or other related experience.
• Deep understanding of HVAC systems especially around industrial controls systems, chiller plants, and airside cooling.
• Previous experience with M&V or data analytics tools.
• Previous experience in a customer adjacent role. Effective soft skills in presenting technical information clearly to customers at all levels of the organization (non-domain experts).
• Natural curiosity and a desire to learn and problem solve when the answer may not…