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Tesla Electronics Test and Automation Group (ETAG) is the main point of contact to ensure the highest quality vehicle, silicon and robotics electronics for our customers. Our mission is to develop test automation equipment, architect software automation framework, and provide hardware/software/data infrastructure for Tesla electronics communities worldwide.
We are seeking a multi-faceted Electrical Engineer who will be responsible for all aspects of validating, identifying, analyzing, root causing, implementing countermeasures, and reporting on issues affecting all low voltage PCBAs from APAC markets. Main components including, but not limited to, body controllers and car computers. This candidate will work with test/design engineers within the group to quickly mitigate and implement countermeasures at suppliers and factories to improve quality, reliability, durability of the products.
The ideal candidate will be a hands-on problem solver with excellent analytical and organizational skills, who thrives in an environment that encourages and rewards superior work. You should be passionate about innovation and developing new skills, and excited to take on the challenge of contributing to the next generation of engineering tools and systems.
Primary Responsibilities
• Work with quality engineers, supplier engineers and suppliers to monitor products performance, identify trending issues. Prioritize based on Severity, occurrence, and/or cost of each failure modes
• Detailed failure analysis, identifying root-cause of problems – Perform board-level debugging to isolate faults for physical FA
• Apply knowledge of electrical engineering and PCBA manufacturing to drive containment and corrective action implementation into production / design / supplier / Firmware.
• Participate in continuous improvement activities and take preventive actions.
• Share Lessons Learned from previous field issues; Provide upfront feedback by participating in design reviews to ensure product performance, reliability, and manufacturability issues are identified and risks mitigated. (DFMEAs)
• Take part in ongoing optimization of the products and processes (performance, cost, technology)
Qualifications / Requirements
• Bachelor's or Master's degree in Electrical, Power Electronics, Electronics, Mechatronic, or similar fields required. MS degree in engineering a plus.
• Preferably in a hands-on role such as Failure Analysis / Quality / Service in consumer electronics or automotive industry
• The successful candidate for this position must have a broad technical background with the ability to work with engineering, manufacturing, service, and suppliers across a wide variety of issues. Strong interpersonal and communication skills are an absolute requirement to establish effective working relationships within Tesla and outside.
• Exceptional problem solving and Failure Analysis, strong attention to detail and analytical thinking.
• Proficient English communication skill in both oral and written skills.
• Proficient in PCBA level troubleshooting and debugging; experience in embedded systems such as ARM microcontroller or FPGA a plus
• Knowledge in applying statistical methods and tools to manage, synthesize, and interpret data.
• Programming Languages & Tools: Python, Minitab, JMP or similar are a strong plus
• Previous experience in a fast-paced, high pressure manufacturing environment a plus.
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About Tesla

Tesla
PublicA 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
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