Phaidra builds AI agents for AI factories, helping data center operators optimize compute, power, cooling, and maintenance for greater performance, reliability, and efficiency. Backed by Index.
About the role
You will work closely with the Technical Program Managers (TPMs) and Data Scientists (DSs), as the technical experts for Phaidra's customers. Your role is to use Phaidra's platform and tools to put AI into production, leading complex, high-impact implementations across multiple customers and environments. This role can be broken down into four concrete areas of responsibility:
What they're looking for
- 10-15 years of work experience as a controls engineer, programmer, or equivalent
- Possesses expertise in HVAC and Data Center cooling control methodologies and strategies and displays knowledge of chiller plant fundamentals, configurations, and sequence of operations
- Has the ability to operate independently as a senior member of the team, managing complex projects across multiple customers
- Understanding of applied thermodynamics for cooling systems, refrigeration systems, and hydronics
- Experience designing, programming, or strong working knowledge of industrial and commercial control systems and protocols such as BACnet and Modbus
- Understanding the applications and control strategies of air side chilled water and direct expansion cooling systems
More about this role
Phaidra is building the future of industrial automation.
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...
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