Data Center Reliability Engineer

🕒 il y a 12 jours

☕ Washington – Distant

☕ Washington – Remote

💵 $101 320 - $163 900 / an

⏰ Temps Plein

🟢 Junior

🟡 Intermédiaire

⛑ Ingénieur DevOps & SRE

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Phaidra

Site WebLinkedInTous les Emplois

51 - 200 employés

🤖 Intelligence artificielle

⚡ Énergie

☁️ SaaS

Artificial Intelligence • Energy • SaaS

Phaidra est une entreprise qui fournit des systèmes de contrôle par intelligence artificielle pour optimiser des installations critiques telles que les centres de données et les usines industrielles. Leur service de contrôle à boucle fermée basé sur l'IA améliore la stabilité des installations, l'efficacité énergétique et la durabilité en réduisant les temps d'arrêt, en augmentant la productivité et en diminuant les émissions de CO2. Contrairement aux systèmes de contrôle traditionnels, les contrôles pilotés par l'IA de Phaidra apprennent continuellement et s'améliorent avec le temps sans nécessiter de nouveau matériel. Le système offre une optimisation en temps réel et s'intègre aux systèmes de contrôle existants, améliorant la sécurité et la stabilité opérationnelle tout en fournissant une transparence totale des données de performance. Phaidra utilise des techniques avancées d'apprentissage par renforcement profond pour obtenir des résultats exceptionnels dans certains des plus grands défis mondiaux, y compris des économies d'énergie significatives dans les centres de données de Google.

Description

• Utilize existing data ingestion and delivery platforms to "teach" models to understand the physical world, filling a critical expertise gap in the data center industry. • Use telemetry tools to analyze sensor data across mechanical (chillers, pumps) and electrical (UPS, switchgear, power feeds) systems to identify "failure signatures" for LLM-driven monitoring tool. • Act as a primary user of platforms, identifying gaps in current mechanisms and collaborating with Engineering to influence future features and data quality. • Translate raw telemetry into "SME-level" logic and directions used by the LLM tool to guide data center operators in real-time. • Cultivate deep domain expertise in all facets of data center infrastructure. • Move from shadowing peers to directly supporting customers, using the platform to provide clear, data-backed direction on complex problems. • Oversee pilot projects to test how AI-driven SME tool interprets real-world stressors, ensuring the output is operationally realistic, accurate, and actionable. • Remain agile and proactive in a fast-moving team environment.

🎯 Exigences

• 2–3 years of professional relevant experience • Bachelor’s degree in Mechanical Engineering, Electrical Engineering, Control Theory, or a related field that provides a foundation in physical systems and thermodynamics. • A deep, innate interest in using data to diagnose how and why systems fail. You are a "tinkerer" who prefers solving real-world problems over theoretical research. • Strong Python skills and experience with data manipulation libraries (Pandas/NumPy) to perform custom analysis outside of standard tooling. • Ability to explain complex diagnostic findings clearly and persuasively to both technical peers and non-domain stakeholders. • A proven ability to look at a problem without preconceived notions and figure out solutions either independently or via team collaboration. • Demonstrated commitment to Transparency, Collaboration, and Ownership—especially in environments where reliability and learning from failure are paramount.

🏖️ Avantages

• Fast-paced, team-oriented environment where your work directly shapes the company’s direction. • We are a 100% remote company. • Competitive compensation & meaningful equity. • Outsized responsibilities & professional development. • Training is foundational; functional, customer immersion, and development training. • Medical, dental, and vision insurance (exact benefits vary by region). • Unlimited paid time off, with a required minimum of 20 days per year. • Paid parental leave (exact benefits vary by region). • Flexible stipends to support your workspace, well-being, and continued professional development. • Company MacBook.