Data Center Electrical Automation Engineer at Lambda

San Francisco, California, United States

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$154,000 – $231,000Compensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Data Centers, AI, Cloud ComputingIndustries

Requirements

Bachelor’s degree in Electrical Engineering or equivalent practical experience
4–6 years of experience in electrical engineering, including power system analysis, relay coordination, and protection logic
Experience with SKM, ETAP, or EasyPower for electrical modeling and study execution
Programming proficiency in Python, C, and 6502 Assembly
Familiarity with KiCad, LTSpice, MATLAB, LabView, Fusion 360, and modern prototyping tools
Hands-on experience with oscilloscopes, DC supplies, logic analyzers, and LCR meters
Strong problem-solving and design instincts — able to translate theory into working systems
Curiosity for automation, solid-state power systems, and integrated data center control environments
Completion of or progress towards a Professional Engineering certification
Nice to Have
Familiarity with 800VDC and Solid-State Transformer (SST) technologies
Experience in BMS/controls integration or IoT-based electrical telemetry
PCB fabrication or hardware prototyping experience
Experience with PLC Industrial Automation languages such as Ladder Logic, Function Block Diagram, Structured Text, etc
Prior work with EPCs, contractors, or consulting firms (e.g., Vertiv, Rosendin)
Understanding of UL891 vs UL1558 vs ANSI/IEEE CS37.20.7 standards/applications
Interest in AI infrastructure design, DCIM development, or energy automation

Responsibilities

Power Systems Analysis (15%) – Perform load flow, short circuit, arc flash, and relay coordination studies on existing sites. Review relay database (.rdb) logic and validate system protection schemes
Automation & Controls Development (20%) – Develop and implement automation frameworks for power capping, oversubscription, and real-time electrical control. Collaborate with software and operations teams on DCIM integration
New Product Introduction (20%) – Support design and layout of emerging electrical systems and switchgear; integrate automation and control logic into new data center prototypes
Delivery & Commissioning (15%) – Participate in co-location delivery reviews, site visits, one-line verification, and field striping plan validation
Hardware Innovation (15%) – Apply PCB design, 3D printing, and embedded programming experience to prototype intelligent hardware modules supporting electrical automation and BMS interfaces
Professional Development (15%) – Broaden your technical range through structured mentorship, expanding into advanced EE domains and next-generation electrical infrastructure

Skills

Power Systems Analysis

Load Flow

Short Circuit

Arc Flash

Relay Coordination

Automation Frameworks

DCIM

PCB Design

Embedded Programming

Switchgear Design

Lambda

Cloud-based GPU services for AI training

About Lambda

Lambda Labs provides cloud-based services for artificial intelligence (AI) training and inference, focusing on large language models and generative AI. Their main product, the AI Developer Cloud, utilizes NVIDIA's GH200 Grace Hopper™ Superchip to deliver efficient and cost-effective GPU resources. Customers can access on-demand and reserved cloud GPUs, which are essential for processing large datasets quickly, with pricing starting at $1.99 per hour for NVIDIA H100 instances. Lambda Labs serves AI developers and companies needing extensive GPU deployments, offering competitive pricing and infrastructure ownership options through their Lambda Echelon service. Additionally, they provide Lambda Stack, a software solution that simplifies the installation and management of AI-related tools for over 50,000 machine learning teams. The goal of Lambda Labs is to support AI development by providing accessible and efficient cloud GPU services.

San Jose, CaliforniaHeadquarters

2012Year Founded

$372.6MTotal Funding

DEBTCompany Stage

AI & Machine LearningIndustries

201-500Employees

Risks

Nebius' holistic cloud platform challenges Lambda's market share in AI infrastructure.

AWS's 896-core instance may draw customers seeking high-performance cloud solutions.

Existential crisis in Hermes 3 model raises concerns about Lambda's AI model reliability.

Differentiation

Lambda offers cost-effective Inference API for AI model deployment without infrastructure maintenance.

Nvidia HGX H100 and Quantum-2 InfiniBand Clusters enhance Lambda's AI model training capabilities.

Lambda's Hermes 3 collaboration showcases advanced AI model development expertise.

Upsides

Inference API launch attracts enterprises seeking low-cost AI deployment solutions.

Nvidia HGX H100 clusters provide competitive edge in high-performance AI computing.

Strong AI cloud service growth indicates rising demand for Lambda's GPU offerings.

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