Phaidra
Industrial Automation
DataCenterReliabilityEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Center Reliability Engineer at Phaidra. Skills: Data Center Reliability, AI Control Systems, Reinforcement Learning. Analyze sensor data across mechanical and electrical systems. Identify failure signatures for LLM-driven monitoring tool”
Industry & Context.
Unbiased problem-solving; Diagnose how and why systems fail
Work hours overlap with APAC
What They're Looking For.
Must Have
2–3 years of professional relevant experience, Bachelor’s degree in Mechanical Engineering, Electrical Engineering, Control Theory, or a related field, Python skills, Experience with data manipulation libraries (Pandas/NumPy), Ability to explain complex diagnostic findings clearly and persuasively, Proven ability to look at a problem without preconceived notions, Demonstrated commitment to Transparency, Collaboration, and Ownership
Nice to Have
U.S. -based team member (Pacific Time Zone preferred), Flexibility to work hours that overlap with APAC time zones, PhD preferred, Specific ML framework experience, Cloud platform certs
What You'll Do.
Analyze sensor data across mechanical and electrical systems
Identify failure signatures for LLM-driven monitoring tool
Refine logic engine mechanisms
Collaborate with Engineering to influence future features
Translate raw telemetry into SME-level logic
Guide data center operators in real-time
Cultivate deep domain expertise in data center infrastructure
Master mechanical and electrical dependencies
Support customers using the platform
Provide data-backed direction on complex problems
Oversee pilot projects to test AI-driven SME tool
Ensure output is operationally realistic
Lean in and solve challenges not explicitly defined
How You'll Work.
Team & Collaboration
Collaborating with Engineering; Shadowing peers; Supporting customers
Communication Scope
Persuasive communication; Clear explanation
Full Job Description
About Phaidra 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 problems. From achieving superhuman performance with DeepMind's AlphaGo, 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’s ability to achieve its mission is determined by our ability to work together — as defined by our core values: Transparency, Collaboration, Operational Excellence, Ownership, and Empathy. We seek individuals who embody these values, as they are instrumental in ensuring our team consistently delivers excellence and fosters an engaging and supportive culture Phaidra is based in the USA, but we are 100% remote with no physical office. We hire employees internationally with the help of our partner, OysterHR. Our team is currently located throughout the USA, Canada, U
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