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Temporary Meta Machine Learning Jobs in Seattle, WA

Research Engineer, MRS AI

Bellevue, WA · On-site

$121K - $181K/yr

Degree must be completed prior to joining Meta • Research experience in machine learning, deep learning, and/or recommender systems, natural language processing • Programming experience in Python ...

... Meta product development Minimum Qualifications • Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, or relevant ...

At Meta, we're building the future of human connection and the technology that enables it. This ... on state-of-the-art machine learning and neural network methodologies • Define, build and ...

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 ...

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 ...

... machine learning and neural network methodologies • Define, build and benchmark new ... Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual ...

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Temporary Meta Machine Learning information

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How much do temporary meta machine learning jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for temporary meta machine learning in Seattle, WA is $25.97, according to ZipRecruiter salary data. Most workers in this role earn between $22.45 and $28.99 per hour, depending on experience, location, and employer.

What are some common challenges faced by professionals in temporary machine learning roles at Meta, and how can they be addressed?

Professionals in temporary machine learning roles at Meta often encounter challenges such as quickly acclimating to complex codebases, integrating with established teams, and delivering impactful results within a limited timeframe. Success in these roles typically requires strong technical skills, adaptability, and effective communication. Proactively seeking guidance, leveraging available documentation, and collaborating closely with permanent team members can help overcome these hurdles and maximize contributions during the temporary assignment.

What is the difference between Temporary Meta Machine Learning vs Data Scientist?

AspectTemporary Meta Machine LearningData Scientist
CredentialsTypically requires a background in computer science, statistics, or related fields; certifications in machine learning or data analysis are commonRequires a degree in computer science, statistics, or related fields; certifications like Certified Data Scientist are advantageous
Work EnvironmentProject-based, often contract roles within tech companies, startups, or consulting firmsFull-time or contract roles in various industries including finance, healthcare, and tech
Industry UsagePrimarily in tech, AI, and machine learning-focused companiesWidely used across multiple industries including finance, healthcare, marketing, and tech

Temporary Meta Machine Learning roles focus on short-term projects involving machine learning model development and deployment, often requiring specialized technical skills. Data Scientist roles are broader, encompassing data analysis, statistical modeling, and insights generation across diverse industries. While both roles require strong analytical skills and technical knowledge, Temporary Meta Machine Learning positions are more specialized in AI and machine learning applications.

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

To thrive as a Temporary Meta Machine Learning Engineer, you need a strong background in computer science, statistics, and machine learning, typically with experience in Python and relevant ML frameworks. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms, and version control systems is often required, along with a proven ability to rapidly learn new technologies. Strong problem-solving skills, adaptability, and effective communication are essential for collaborating within dynamic teams and meeting project goals on tight timelines. These skills ensure that you can quickly contribute to impactful ML projects, deliver results efficiently, and integrate well into fast-paced, innovative environments.

What are Temporary Meta Machine Learning jobs?

Temporary Meta Machine Learning jobs are short-term positions at Meta (formerly Facebook) that focus on developing, deploying, or researching machine learning models and technologies. These roles may support ongoing projects, fill gaps during employee leave, or address spikes in workload. Responsibilities can include data preprocessing, model training, evaluation, and collaborating with cross-functional teams. Temporary roles often give candidates exposure to Meta's cutting-edge AI tools and processes, and may sometimes lead to permanent opportunities.
What are the most commonly searched types of Meta Machine Learning jobs in Seattle, WA? The most popular types of Meta Machine Learning jobs in Seattle, WA are:
What job categories do people searching Temporary Meta Machine Learning jobs in Seattle, WA look for? The top searched job categories for Temporary Meta Machine Learning jobs in Seattle, WA are:
Infographic showing various Temporary Meta Machine Learning job openings in Seattle, WA as of May 2026, with employment types broken down into 73% Full Time, 11% Part Time, 5% Temporary, and 11% Contract. Highlights an 73% Physical, 10% Hybrid, and 17% Remote job distribution, with an average salary of $54,020 per year, or $26 per hour.
Research Engineer, MRS AI

Research Engineer, MRS AI

Meta

Bellevue, WA • On-site

$121K - $181K/yr

Full-time

Posted 7 days ago


Meta rating

7.5

Company rating: 7.5 out of 10

Based on 43 frontline employees who took The Breakroom Quiz

120th of 186 rated software companies


Job description

Meta is seeking a Research Engineer to join our Meta Recommendation Systems (MRS) AI Algorithm Team. Join us to build Meta's User Intelligence Engine - a unified platform that models who the user is, what they need, and why they act by integrating state, representation, reasoning, and multi-architecture modeling to power Meta's Recommendation System with personalized, context-aware experiences across the ecosystem. We're bringing together two powerhouses: - Generative AI/LLMs for semantic understanding and reasoning - Meta's world-class ads & organic ranking expertise for optimized decision-making at scale As part of a rapidly growing ML team, you'll shape the next generation of User Understanding models and Meta Recommendation Systems, delivering personalization that feels intuitive, adaptive, and truly human.
Responsibilities
Develop and implement large-scale model architectures, leveraging model scaling and transfer learning techniques
• Prioritize training scalability and signal scaling to optimize model performance, efficiency, and reliability
• Develop and apply NextGen sequence learning techniques to drive advancements in recommender systems and machine learning
• Design and implement generative modeling solutions for data augmentation
• Develop and deploy machine learning pipelines
• Develop and implement innovative solutions for data-related challenges, utilizing knowledge of semi/self-supervised learning, generative techniques, sampling, debiasing, domain adaptation, continual learning, data augmentation, cold-start, content understanding, and large language models
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
• Research experience in machine learning, deep learning, and/or recommender systems, natural language processing
• Programming experience in Python and hands-on experience with frameworks such as PyTorch
• Exposure to architectural patterns of large scale software applications
Preferred Qualifications
• 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
• Master's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• A PhD in AI, computer science, data science, or related technical fields
• First author publications at peer-reviewed AI conferences (e.g., NeurIPS, ICML, ICLR, RecSys, SIGIR, KDD, WSDM, TheWebConf, ICDM, ACL, EMNLP, NAACL, AAAI, ICCV, CVPR)
• Direct experience in generative AI, LLMs, RecSys, ML research
• Experience with developing large-scale machine learning models from inception to business impact
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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