Research Engineer, AI Specialist - FAIR

Meta

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

San Francisco, CA, USA • Seattle, WA, USA

$70,670 - $208,000

Machine Learning

Senior Software Engineer

In-Person

5,000+ Employees

3+ years of experience

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Description For Research Engineer, AI Specialist - FAIR

Meta is seeking an experienced AI Research Engineer to join their Fundamental AI Research Organization (FAIR), offering an exciting opportunity to work on cutting-edge artificial intelligence solutions. This role combines academic research with practical applications, focusing on some of the most challenging social data and prediction problems on the web.

The position requires a strong foundation in machine learning, with expertise in areas such as computer vision, NLP, and conversational AI. The ideal candidate will have at least 3 years of specialized experience in machine learning domains, along with advanced education in AI or related fields. The role involves developing novel AI algorithms, building intelligent systems, and creating methodologies to evaluate different approaches.

At Meta, you'll be part of a team that's pushing the boundaries of AI technology, working on projects that directly impact billions of users across platforms like Facebook, Instagram, WhatsApp, and Meta's AR/VR initiatives. The company offers competitive compensation, including a base salary range of $70,670 to $208,000, plus bonus and equity opportunities.

The role is based in either Menlo Park, CA or Seattle, WA, offering the chance to work in major tech hubs alongside world-class AI researchers and engineers. Meta provides a comprehensive benefits package and maintains a strong commitment to diversity, equality, and inclusion in their hiring practices.

This is an exceptional opportunity for someone looking to make a significant impact in the field of AI while working on large-scale applications that affect how people connect and interact globally. The position offers the perfect blend of research and practical implementation, making it ideal for candidates who want to push the boundaries of AI technology while seeing their work deployed at scale.

Last updated 2 months ago

Responsibilities For Research Engineer, AI Specialist - FAIR

Apply relevant AI and machine learning techniques to build intelligent agentic systems that improve Meta's products and experiences
Develop novel, accurate, and safe AI algorithms and advanced systems for large scale applications
Define use cases and develop methodology and benchmarks to evaluate different approaches

Requirements For Research Engineer, AI Specialist - FAIR

Python

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
A Masters in AI, computer science, data science, or related technical fields
3+ years of specialization experience in machine learning domains
In-depth understanding in mainstream ML domains such as computer vision, NLP, conversational AI
ML theory: reinforcement learning, privacy preserving machine learning, large scale personalization, machine learning fairness, machine learning interpretability, machine learning robustness

Benefits For Research Engineer, AI Specialist - FAIR

Medical Insurance

Dental Insurance

Vision Insurance

bonus
equity
benefits

Meta

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

San Francisco, CA, USA • Seattle, WA, USA

$70,670 - $208,000

Machine Learning

Senior Software Engineer

In-Person

5,000+ Employees

3+ years of experience

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?

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Binary Search

Meta

How would you design a duplicate file finder, discussing complexity, optimizations, and trade-offs?

System DesignHard

Let's design a system utility to find duplicate files on a given file system. The utility should traverse a directory, compute a hash for each file, and identify duplicates based on these hashes. Discuss the algorithmic complexity, potential optimizations, and trade-offs between CPU and RAM usage. What is the theoretical best performance we can achieve?

Arrays

Strings

Greedy Algorithms

Dynamic Programming

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Meta

How would you handle a team facing individual performance issues, lack of direction, and code ownership conflicts?

Behavioral

Let's say you are managing a team of five engineers working on a critical feature for an upcoming product launch. One of your engineers, Sarah, consistently delivers high-quality work but has been missing deadlines lately. During a one-on-one meeting, Sarah confides in you that she is feeling overwhelmed with her workload due to personal issues outside of work. Additionally, another engineer, David, has been expressing frustration about the lack of clear direction and feeling that his skills are not being fully utilized. Furthermore, the team is starting to experience conflicts regarding code ownership and integration, leading to delays and tension. As the engineering manager, how would you address these issues to ensure the successful delivery of the feature while maintaining a positive and productive team environment? Please provide specific steps and strategies you would implement to handle each situation, including Sarah's performance, David's concerns, and the team's conflict.

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