Research Engineer, ML, AI & Computer Vision

Meta
City of London
4 months ago
Applications closed

Related Jobs

View all jobs

Sr Research Engineer, Computer Vision

Sr Research Engineer, Computer Vision

Research Engineer: Graph Machine Learning

Machine Learning Research Engineer

Machine Learning Research Engineer – NLP / LLM

Machine Learning Research Engineer – NLP / LLM

Overview

Summary: Meta Reality Labs Research (RL Research) brings together a world-class R&D team of researchers, developers, and engineers with the shared goal of developing AI and AR/VR technology across the spectrum. The Surreal Spatial AI group is seeking high-performing research engineers to build machine perception technology allowing AI agents and systems to perceive and understand the 3D world around them. The aim of this role is to develop, advance and integrate ML and computer vision models and SW systems for advanced, full-stack, real-time, Machine Perception and AI prototypes for egocentric devices such as Meta's Project Aria; Including 3D environment and object reconstruction, semantic understanding as well as estimation and understanding of user motion, actions and activities.

Responsibilities
  1. Implement and prototype advanced research systems and technologies spanning device and cloud, in the domain of AI and machine perception
  2. Collaborate with team members throughout the lifetime of a project, from early research through technology and experience prototyping
  3. Play a critical role in the definition and execution of system research roadmaps in partnership and cross functional organizations in computer vision, machine learning, graphics, sensors, optics and silicon
  4. Collaborate with cross-functional engineering and research teams from Reality Labs and FAIR in computer vision, machine learning, and graphics
Minimum Qualifications
  1. Bachelor's degree in Computer Science, Computer Vision, Robotics or a related technical field
  2. Experience in one or more of the following areas: Deep Learning, Computer Vision, AR/VR, 3D Vision, Robotics, Machine Learning or artificial intelligence
  3. Experience developing computer vision algorithms or computer vision infrastructure in C/C++ or Python
Preferred Qualifications
  1. Experience with distributed systems or on-device algorithm development
  2. Industry experience working on projects such as: real-time Simultaneous Localization and Mapping and 3D reconstruction, sensor fusion and active depth sensing, object and body tracking and pose estimation, and/or image processing.
  3. Experience in deep learning and PyTorch
  4. MSc or PhD degree in Computer Science, Computer Vision, Machine Learning, Robotics or related technical field.

Industry: Internet


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

Jobs

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

Education

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.