Research Engineer, ML, AI & Computer Vision

Meta
London
1 week ago
Create job alert

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 scientists 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, estimation and understanding of user motion, actions and activities.


Research Engineer, ML, AI & Computer Vision Responsibilities

  • Implement and prototype advanced research systems and technologies spanning device and cloud, in the domain of AI and machine perception.
  • Collaborate with team members throughout the lifetime of a project, from early research through technology and experience prototyping.
  • 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.
  • Collaborate with cross-functional engineering and research teams from Reality Labs and FAIR in computer vision, machine learning, and graphics.

Minimum Qualifications

  • MSc or PhD degree in Computer Science, Computer Vision, Robotics or a related technical field.
  • Experience developing and designing Computer Vision and Perception for Robotics or smart device technologies and systems.
  • 5+ years of experience with a mastery of modern features in C++.
  • Experience working in a Unix environment.
  • Interpersonal experience: cross-group and cross-functional collaboration.

Preferred Qualifications

  • Industry experience working on projects such as: real-time SLAM and 3D reconstruction, scene understanding, robotics and agentic AI systems including autonomous driving.
  • Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g., GitHub).
  • Broad experience with distributed systems, cloud services, or on-device algorithm development.
  • 3+ years of industry or postdoctoral experience as full-stack software engineer.

About Meta

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics.


Equal Employment Opportunity

Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here.

Meta is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, fill out the Accommodations request form.

#J-18808-Ljbffr

Related Jobs

View all jobs

Research Engineer, ML, AI & Computer Vision

Research Engineer

Computer Vision Development Engineer

Machine Learning Engineer

Research/Compiler Engineer

Computer Vision Engineer - Contract (inside)

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Machine Learning Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Machine learning (ML) has become an indispensable force in the modern business world, influencing everything from targeted marketing campaigns to advanced medical diagnostics. As industries integrate predictive algorithms and data-driven decision-making into their core operations, the need for effective leadership in machine learning environments has never been greater. Whether you’re overseeing a small team of data scientists or spearheading an enterprise-scale ML project, your leadership style must accommodate rapid innovation, complex problem-solving, and diverse stakeholder expectations. This guide provides actionable insights into how you can motivate, mentor, and establish achievable goals for your machine learning teams—ensuring they thrive in data-driven environments.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.