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Facebook Machine Learning Jobs (NOW HIRING)

Meta

Product Manager, Machine Learning

Menlo Park, CA

$173K/yr

Understand Facebook's strategic and competitive position and deliver products that are aligned with ... in Machine Learning * Requires a Bachelor's degree (or foreign degree equivalent) in Computer ...

Meta

Product Manager, Machine Learning

Sunnyvale, CA

$173K/yr

Understand Facebook's strategic and competitive position and deliver products that are aligned with ... in Machine Learning * Requires a Bachelor's degree (or foreign degree equivalent) in Computer ...

Meta

Product Manager, Machine Learning

New York, NY

$173K/yr

Understand Facebook's strategic and competitive position and deliver products that are aligned with ... in Machine Learning * Requires a Bachelor's degree (or foreign degree equivalent) in Computer ...

Meta

Product Manager, Machine Learning

Bellevue, WA

$173K/yr

Understand Facebook's strategic and competitive position and deliver products that are aligned with ... in Machine Learning * Requires a Bachelor's degree (or foreign degree equivalent) in Computer ...

NYULMC

Machine Learning Engineer

New York, NY ยท On-site

... Glassdoor, Indeed, Facebook, Twitter and Instagram. Position Summary: We have an exciting ... As a ML Engineer, you will support the implementation of diverse Generative AI and Machine Learning ...

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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 14, 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
What job categories do people searching Facebook Machine Learning jobs look for? The top searched job categories for Facebook Machine Learning jobs are:
Facebook Machine Learning jobs near you
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.