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Meta Machine Learning Jobs (NOW HIRING)

... Meta, LinkedIn, Coinbase, Square, and Goldman Sachs. Hang raised a $16 million Series A led by ... This person will implement and develop machine learning models to enhance our platform ...

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine ... Fine-tune large language models (LLMs) and implement meta-learning methods to enhance model ...

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How much do meta machine learning jobs pay per hour?

As of Jul 23, 2026, the average hourly pay for meta machine learning in the United States is $21.33, according to ZipRecruiter salary data. Most workers in this role earn between $18.75 and $22.84 per hour, depending on experience, location, and employer.

What is a Meta Machine Learning job?

A Meta Machine Learning job typically involves developing and optimizing machine learning models at scale, often within Meta (formerly Facebook). These roles focus on improving AI algorithms, researching new techniques, and deploying models across products like Facebook, Instagram, and WhatsApp. Engineers and researchers in this field work with large datasets, deep learning frameworks, and distributed computing. The role requires expertise in machine learning, software engineering, and data science to enhance Meta's AI-driven capabilities.

What are the key skills and qualifications needed to thrive in the Meta Machine Learning position, and why are they important?

To thrive in Meta Machine Learning, you need a deep understanding of advanced machine learning algorithms, meta-learning techniques, data science, and a degree in computer science or a related field. Experience with tools like Python, TensorFlow, PyTorch, as well as familiarity with cloud computing platforms and relevant certifications (such as AWS Certified Machine Learning Specialty) are highly valuable. Strong analytical thinking, creative problem-solving, and collaborative communication are essential soft skills for excelling in this area. These competencies enable practitioners to develop and optimize meta-learning models, drive innovation, and efficiently work in cross-functional tech teams.

What are some of the main challenges faced in a Meta Machine Learning role?

Professionals in Meta Machine Learning often encounter challenges such as working with limited labeled data, creating models that generalize well across diverse tasks, and optimizing algorithms to learn efficiently from smaller datasets. The fast-paced nature of research and the need to stay updated with cutting-edge advancements in the field can also require continual learning and adaptation. Collaboration with other data scientists, engineers, and domain experts is common, making teamwork and clear communication critical for successful project delivery. Overcoming these challenges not only sharpens technical skills but also offers rewarding opportunities for innovation and career growth in this evolving field.

More about Meta Machine Learning jobs
What cities are hiring for Meta Machine Learning jobs? Cities with the most Meta Machine Learning job openings:
What are the most commonly searched types of Meta Machine Learning jobs? The most popular types of Meta Machine Learning jobs are:
What states have the most Meta Machine Learning jobs? States with the most job openings for Meta Machine Learning jobs include:
Infographic showing various Meta Machine Learning job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $44,363 per year, or $21.3 per hour.
Visiting Researcher, Meta Superintelligence Labs

Visiting Researcher, Meta Superintelligence Labs

Meta

Menlo Park, CA • On-site

$58.65/hr

Full-time

Posted 7 days ago


Meta rating

7.5

Company rating: 7.5 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

140th of 215 rated software companies


Job description

Meta is seeking a Visiting Researcher to join Meta Superintelligence Labs. Individuals in this role are proficient in identified research areas such as artificial intelligence, machine learning, robotics, and embodied AI, particularly including areas such as transfer learning, learning from demonstration, reinforcement learning, action-conditioned world models, perception, representation learning, robot control, navigation, mobile manipulation, dexterous manipulation, and vision-language models. You should have a keen interest in producing new, open science to make embodied agents more intelligent.
Responsibilities
Perform fundamental and applied research to push the scientific and technological frontiers of embodied artificial intelligence
• Invent/improve novel data-driven paradigms for robotics, leveraging a variety of modalities (images, video, text, audio, tactile, etc)
• Investigate paradigms that can deliver a spectrum of embodied behaviors - from simulated characters to real robots, and from short-horizon, low-level to long-horizon, high-level intelligence
• Develop algorithms based on state-of-the-art machine learning and neural network methodologies
• Build and benchmark new capabilities needed for the next generation of AI
• Conduct research towards long-term research goals while identifying intermediate milestones
• Execute on novel research based on long-term objectives of the organization
Minimum Qualifications
• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
• Experience with any of the following research areas: robotics, motion planning, embodied AI, human-robot interaction, sim-to-real transfer, learning from demonstration, reinforcement learning, dexterous manipulation, digital agents, vision language models, computer vision, egocentric perception, and/or LLMs
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
Preferred Qualifications
• Currently has, or is in the process of obtaining a Master's or PhD degree in the field of Artificial Intelligence, Robotics, Computer Vision, Machine Learning, Language, a related field, or equivalent practical experience
• Experience with deep learning frameworks (such as PyTorch, TensorFlow) and Python
• Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
• Experience building systems based on machine learning and/or deep learning methods
• Experience in relevant robotics-related research areas, such as: robot learning, reinforcement learning, imitation learning, action-conditioned world models, task and motion planning, sim-to-real transfer, robotic control, manipulation, navigation, or generally embodied AI
• Experience working and communicating cross-functionally in a team environment
• Experience with manipulating and analyzing complex, large-scale, high-dimensionality data from varying sources
• Experience with robotics frameworks like ROS, along with experience working with robot simulations and real-world hardware
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.

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