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Facebook Machine Learning Jobs (NOW HIRING)

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Facebook Machine Learning information

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How much do facebook machine learning jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for facebook 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 the difference between Facebook Machine Learning vs Data Scientist?

AspectFacebook Machine LearningData Scientist
Required CredentialsDegree in Computer Science, Data Science, or related fields; experience with ML frameworksDegree in Statistics, Mathematics, Computer Science, or related fields; strong analytical skills
Work EnvironmentTech company, collaborative teams, focus on ML models and algorithmsVaried industries, data analysis, reporting, and insights generation
Employer & Industry UsagePrimarily in tech companies like Facebook, focusing on AI/ML productsAcross industries including tech, finance, healthcare, focusing on data analysis

Facebook Machine Learning specialists focus on developing and deploying machine learning models within Facebook's infrastructure, requiring strong programming and ML skills. Data Scientists analyze data to generate insights, often using statistical methods. While both roles require a background in data or computer science, Facebook Machine Learning roles are more technical and model-focused, whereas Data Scientists emphasize data analysis and interpretation.

What does a Facebook Machine Learning Engineer do?

A Facebook Machine Learning Engineer designs, builds, and deploys artificial intelligence models that power various features and products across Meta's platforms, such as Facebook, Instagram, and WhatsApp. Their work involves data preprocessing, model selection, training, evaluation, and optimization to improve user experiences like content recommendations, spam detection, and ad targeting. They also collaborate with product managers, researchers, and software engineers to integrate these models into scalable systems. The role requires strong programming skills, knowledge of machine learning algorithms, and experience with large-scale data processing.

What are the key skills and qualifications needed to thrive as a Facebook Machine Learning Engineer, and why are they important?

To thrive as a Facebook Machine Learning Engineer, you need a strong background in computer science, statistics, and machine learning, usually backed by a relevant degree and experience in large-scale data analysis. Proficiency in Python, C++, TensorFlow or PyTorch, and experience with distributed computing systems are typically required. Strong problem-solving skills, collaboration, and effective communication help you work cross-functionally and drive innovative solutions. These skills enable the rapid development and deployment of impactful machine learning models at scale, which is crucial for Facebook's data-driven products and services.

How does a Facebook Machine Learning Engineer typically collaborate with product teams to deploy models into production?

As a Facebook Machine Learning Engineer, you will work closely with product managers, software engineers, and data scientists to integrate machine learning solutions into real-world products. This often involves participating in cross-functional meetings to understand product requirements, iterating on model prototypes, and ensuring smooth deployment and monitoring of models in production. Collaboration is key, as you will need to communicate technical insights to non-technical stakeholders and incorporate feedback to improve model performance. This dynamic environment provides opportunities to learn from experts across multiple domains and contribute directly to impactful, large-scale products.
More about Facebook Machine Learning jobs
Infographic showing various Facebook Machine Learning job openings in the United States as of July 2026, with employment types broken down into 2% As Needed, 75% Full Time, 14% Part Time, 1% Temporary, and 8% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $44,363 per year, or $21.3 per hour.
Software Engineer, Machine Learning RecSys

Software Engineer, Machine Learning RecSys

Meta

Bellevue, WA • On-site, Remote

$154K/yr

Full-time

Posted 16 days ago


Meta rating

7.5

Company rating: 7.5 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

135th of 209 rated software companies


Job description

Meta is seeking talented Machine Learning engineers to join our teams in building cutting-edge products, with the mission of connecting billions of people around the world. As a member of our team, you will have the opportunity to work on complex technical problems, build new features, and improve existing products across various platforms, including mobile devices and web applications. Our teams are constantly pushing the boundaries of user experience, and we're looking for passionate individuals who can help us advance the way people connect globally. If you're interested in joining a world-class team and working on exciting projects that have a significant impact, we encourage you to apply.
Software Engineer, Machine Learning RecSys Responsibilities:
  • Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences.
  • Implement custom user interfaces using latest programming techniques and technologies.
  • Develop reusable software components for interfacing with back-end platforms.
  • Analyze and optimize code for quality, efficiency, and performance.
  • Lead complex technical or product efforts and provide technical guidance to peers.
  • Architect efficient and scalable systems that drive complex applications.
  • Identify and resolve performance and scalability issues.
  • Work on a variety of coding languages and technologies.
  • Establish ownership of components, features, or systems with expert end-to-end understanding.

Minimum Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 2+ years of programming experience in a relevant programming language
  • 1+ years of hands-on experience in one or more of the following areas: machine learning, recommendation systems, llms or artificial intelligence
  • Experience with scripting languages such as Python, Javascript or Hack
  • Experience with developing machine learning models at scale from inception to business impact
  • Knowledge developing and debugging in C/C++ and Java, or experience with scripting languages such as Python, Perl, PHP, and/or shell scripts
  • Track record of setting technical direction for a team, driving consensus and successful cross-functional partnerships
  • Proven experience designing, building, or deploying recommendation systems (e.g., collaborative filtering, content-based, hybrid approaches, personalization at scale)
  • Experience building and shipping high quality work and achieving high reliability
  • Experience improving quality through thoughtful code reviews, appropriate testing, proper rollout, monitoring, and proactive changes

Preferred Qualifications:
  • Masters degree or PhD in Computer Science or another ML-related field
  • Exposure to architectural patterns of large scale software applications
  • Experience with scripting languages such as Pytorch and TensorFlow
  • Publications in top-tier conferences/journals, patents, or open-source contributions in the recommendations or LLM space
  • Hands-on experience working with large language models (LLMs), such as BERT, GPT, or similar architectures, including fine-tuning, integration, or application in production environments
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

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.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$154,003/year to $217,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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