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Equipment Maintenance Technician, LFP Cell Manufacturing

Tesla

Equipment Maintenance Technician, LFP Cell Manufacturing

Tesla

Sparks, Nevada

·

On-site

·

Full-time

·

Today

What to Expect

Tesla is seeking highly motivated Equipment Maintenance Technicians who will play a crucial role in ensuring the operational availability of our advanced battery cell manufacturing equipment. The Equipment Maintenance Technician will apply their technical skills to install, maintain and repair high speed, high volume mechanical and electrical systems, factory automation and robotics. They will be the first-responding problem solvers who manage machine breakdowns and recoveries.

What You'll Do

  • Perform repairs, rebuilds, installations and preventative maintenance (PM) on all industrial production equipment
  • Diagnose the root cause of equipment failures and communicate required corrective actions across relevant teams
  • Collaborate with Process and Equipment Engineering teams to improve equipment reliability and maintenance protocols
  • Perform corrective maintenance (repairs) on more than one of these types of equipment: Electrical systems ranging from 24 VDC to 480 VAC 3 phase, Mechanical systems, Conveyor Systems, Hydraulics, Pneumatics / Vacuum Systems, PLC and networks (Allen Bradley / Siemens / Beckhoff), Vison/Inspection Equipment (Keyence / XRAY / Surface inspectors) and Fanuc/Kuka robots
  • Order parts, supplies and equipment from catalogues and suppliers or obtain them from storerooms
  • Log all work as performed utilizing Tesla CMMS

What You'll Bring

  • Four (4) or more years of experience working in a maintenance capacity on industrial production manufacturing equipment or equivalent education/ training
  • Demonstrate ability to analyze problems, identify root causes and implement viable long-term solutions
  • Experience with troubleshooting complex mechanical systems (drive gears, hydraulic, pneumatic) and complex electrical systems (servo motors, VFDs, PLC I/O)
  • Follow all aspects of maintenance safety protocol (LOTO, 6s, Arc Flash)
  • Must have command of the English language, both written and verbal
Essential Physical Demands
  • Ability to perform physically demanding work for extended periods of time, up to 12 hours a day
  • Ability to stand and walk for up to 12 hours a day, including over varied and uneven terrain
  • Frequently and repetitively, lift, push and carry up to 35 lbs, including the ability to carry 20 lbs up and down stairs 
  • Frequently and repetitively, bend, lift and reach 
  • Stoop, lay, bend, reach, squat, kneel, crouch, twist and crawl for extended periods of time, including up to 12 hours a day 
  • Climb and maintain balance on ladders, scaffolding or other high structures 
  • Ability to find issues in a work process and receive safety signals using sight, touch, or hearing
  • Wearing Personal Protective Equipment, including but not limited to: PAPR, safety glasses, safety shoes, bump caps, and adhering to prescribed safety rules and guidelines

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About Tesla

Tesla

Tesla

Public

A financial leasing taxi company that provides vehicles to customers

140,000+

Employees

Ciudad De Panamá

Headquarters

$800B

Valuation

Reviews

3.1

5 reviews

Work Life Balance

1.5

Compensation

1.2

Culture

1.3

Career

1.8

Management

1.1

15%

Recommend to a Friend

Pros

Strong financial performance

Revenue growth

Company achieving targets

Cons

Poor compensation and raises below inflation

Union-busting and anti-labor practices

Unpaid work demands and wage theft

Salary Ranges

3,570 data points

Junior/L3

Mid/L4

Junior/L3 · Associate Analyst

2 reports

$94,875

total / year

Base

$82,500

Stock

-

Bonus

-

$92,000

$97,750

Interview Experience

4 interviews

Difficulty

3.5

/ 5

Duration

14-28 weeks

Experience

Positive 0%

Neutral 75%

Negative 25%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Take-home Assignment

5

Panel Interview

6

Offer

Common Questions

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

System Design

Machine Learning Concepts