HW Reliability Engineer Intern (BS/Masters)

Meta

Meta builds technologies that help people connect, find communities, and grow businesses through social technology and immersive experiences.

San Francisco, CA, USA

Data

Software Engineering Intern

In-Person

5,000+ Employees

AR/VR

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Description For HW Reliability Engineer Intern (BS/Masters)

Meta Reality Labs is at the forefront of developing hardware for next-generation virtual, augmented, and mixed reality experiences. As a HW Reliability Engineer Intern, you'll be part of a dynamic team working on bringing together reliability data from multiple sources to develop insight-rich dashboards. This 12-16 week internship offers hands-on experience in reliability engineering, data analysis, and dashboard development.

The role combines technical expertise in data science with reliability engineering principles, offering exposure to cutting-edge AR/VR technology development. You'll work with advanced tools and technologies while contributing to Meta's mission of building the future of social connection through immersive experiences.

This position is perfect for engineering students passionate about data analysis, reliability engineering, and emerging technologies. You'll have the opportunity to work with state-of-the-art tools, present findings to leadership, and gain valuable experience in a leading tech company. The role offers hands-on experience with real-world applications of reliability engineering principles and data science in the context of AR/VR hardware development.

Meta offers a collaborative environment where interns can learn from industry experts, work on meaningful projects, and contribute to the development of revolutionary technology. This internship is ideal for those looking to apply their academic knowledge in a practical setting while gaining exposure to the latest developments in AR/VR technology.

Last updated 3 months ago

Responsibilities For HW Reliability Engineer Intern (BS/Masters)

Source reliability data from disparate sources to create insights
Develop dynamic and durable dashboards that are derived from evolving datasets
Drive risk model improvements and model input refinement
Present insights to leadership team

Requirements For HW Reliability Engineer Intern (BS/Masters)

Python

Currently pursuing a Bachelors degree in engineering or science
Experience in data science skills and basic programming: Tableau, JMP, SQL, Python / R and Google suite
Working analytical and problem-solving skills
Effective communication and collaboration skills
Ability to work independently and as part of a team
Must obtain work authorization in country of employment

Benefits For HW Reliability Engineer Intern (BS/Masters)

Medical Insurance

Dental Insurance

Vision Insurance

Competitive compensation
Health benefits

Meta

Meta builds technologies that help people connect, find communities, and grow businesses through social technology and immersive experiences.

San Francisco, CA, USA

Data

Software Engineering Intern

In-Person

5,000+ Employees

AR/VR

Meta

Snapshot Array

Data Structures & AlgorithmsMedium

Implement a SnapshotArray that supports the following interface: SnapshotArray(int length) initializes an array-like data structure with the given length. Initially, each element equals 0. void set(index, val) sets the element at the given index to be equal to val. int snap() takes a snapshot of the array and returns the snap_id: the total number of times we called snap() minus 1. int get(index, snap_id) returns the value at the given index, at the time we took the snapshot with the given snap_id For example: Input: [SnapshotArray,set,snap,set,get] [[3],[0,5],[],[0,6],[0,0]] Output: [null,null,0,null,5] Explanation: SnapshotArray snapshotArr = new SnapshotArray(3); // set the length to be 3 snapshotArr.set(0,5); // Set array[0] = 5 snapshotArr.snap(); // Take a snapshot, return snap_id = 0 snapshotArr.set(0,6); snapshotArr.get(0,0); // Get the value of array[0] with snap_id = 0, return 5 What data structures and algorithms are best suited for this problem? What are the time and space complexities of each operation?

Arrays

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Design a high data volume real-time data pipeline.

System DesignMedium

Design a high data volume real-time data pipeline, discussing both high-level and low-level details. For example, imagine you're building a real-time clickstream processing pipeline for an e-commerce website that receives millions of clicks per minute. The pipeline needs to process this data to provide real-time insights such as top-selling products, website traffic analysis, and fraud detection. Consider aspects such as data ingestion, storage, processing, and serving. Discuss the technologies you would choose for each stage and justify your choices. Also, address potential challenges like data volume, velocity, variety, and veracity. How would you ensure the pipeline is scalable, reliable, and fault-tolerant? What monitoring and alerting mechanisms would you implement? How would you handle backpressure and ensure data consistency? Finally, how would you optimize the pipeline for cost-effectiveness and performance?

Database Problems

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Where are you from?

Behavioral

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