Research Scientist, Machine Learning

Meta; Seattle (WA); On-site; USD 122,000 - 181,000; Full time

Job summary

Meta is seeking a Research Scientist to join the Core Machine Learning Research team, advancing foundational AI and ML technologies at scale. You will conduct original research in deep learning, representation learning, generative modeling, and optimization, collaborating with researchers and engineers to translate findings into real-world impact.

You will design and implement novel ML algorithms using PyTorch/TensorFlow, run rigorous experiments, and contribute to reproducible research.

Qualifications

• Bachelor's degree in CS or related field completed before joining Meta.
• PhD in ML/AI/CS/Statistics or related field completed before joining Meta.
• Work authorization in the country of employment at time of hire.
• 2+ years of ML research experience with deep learning frameworks such as PyTorch or TensorFlow.
• 2+ years of Python or C++ for ML research and systems development.

Responsibilities

• Conduct original research in core machine learning areas including deep learning, representation learning, generative modeling, optimization, and large-scale model architectures.
• Design, implement, and evaluate novel ML algorithms and models using frameworks such as PyTorch, iterating based on experimental results and data-driven insights.
• Run controlled experiments to test research hypotheses, analyze outcomes, and make informed decisions in collaboration with research and engineering partners.
• Write clean, well-structured research code and contribute to shared codebases, ensuring reproducibility and maintainability of experiments.
• Produce and submit research findings to top-tier machine learning conferences and workshops such as NeurIPS, ICML, ICLR, or similar venues.
• Collaborate with cross-functional partners across research, engineering, and product teams to integrate research innovations into production systems at scale.
• Participate in code and design reviews, providing and incorporating technical feedback to improve research quality and implementation robustness.
• Build logging, monitoring, and evaluation pipelines to track model performance and detect regressions during research and deployment phases.
• Contribute to the health of the research community by participating in programs such as reading groups, research reviews, and onboarding support for incoming researchers.

Skills

Communication of research findings

Team collaboration

Critical thinking

Education

Bachelor's degree in CS or related field

PhD in ML/AI/CS/Statistics or related

Tools

PyTorch

TensorFlow

Python

C++

Job description

Summary:

Meta is seeking a Research Scientist to join our Core Machine Learning Research team, where we advance the foundational AI and ML technologies that power Meta's family of products at scale. In this role, you will conduct original research in areas such as deep learning, representation learning, generative modeling, optimization, and large-scale model architectures. You will collaborate closely with researchers and engineers across the organization to translate novel findings into real-world impact, publish at top-tier venues, and help shape the direction of machine learning research at Meta.

Required Skills:

Research Scientist, Machine Learning Responsibilities:

1. Conduct original research in core machine learning areas including deep learning, representation learning, generative modeling, optimization, and large-scale model architectures
2. Design, implement, and evaluate novel ML algorithms and models using frameworks such as PyTorch, iterating based on experimental results and data-driven insights
3. Run controlled experiments to test research hypotheses, analyze outcomes, and make informed decisions in collaboration with research and engineering partners
4. Write clean, well-structured research code and contribute to shared codebases, ensuring reproducibility and maintainability of experiments
5. Produce and submit research findings to top-tier machine learning conferences and workshops such as NeurIPS, ICML, ICLR, or similar venues
6. Collaborate with cross-functional partners across research, engineering, and product teams to integrate research innovations into production systems at scale
7. Participate in code and design reviews, providing and incorporating technical feedback to improve research quality and implementation robustness
8. Build logging, monitoring, and evaluation pipelines to track model performance and detect regressions during research and deployment phases
9. Contribute to the health of the research community by participating in programs such as reading groups, research reviews, and onboarding support for incoming researchers

Minimum Qualifications:

Minimum Qualifications:

1. 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
2. Currently has, or is in the process of obtaining, a PhD degree in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, or a related technical field. Degree must be completed prior to joining Meta
3. Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
4. 2+ years of research experience in machine learning, including designing and implementing novel algorithms using deep learning frameworks such as PyTorch or TensorFlow
5. 2+ years of experience with Python or C++ for research and systems development in machine learning contexts
6. Experience conducting experiments to validate research hypotheses and communicating findings through written papers, technical reports, or presentations

Preferred Qualifications:

Preferred Qualifications:

1. Demonstrated software engineering experience through open-source contributions, research internships, or widely adopted research implementations
2. Experience manipulating and analyzing large-scale, high-dimensional datasets for model training and evaluation
3. Research experience in one or more specialized areas including large language models, self-supervised learning, reinforcement learning, causal inference, graph neural networks, or ML systems and hardware-software co-design
4. Proven research contributions demonstrated by first-authored publications at leading venues such as NeurIPS, ICML, ICLR, AAAI, CVPR, ACL, or similar conferences

Public Compensation:

$122,000/year to $181,000/year + bonus + equity + benefits

Industry: Internet

Equal Opportunity:

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