Research Scientist, Machine Learning for Monetization (PhD)
Menlo Park, CAJob$122–181K/yrSeen 1mo agoSeen in employer's feed today
Most applications go out cold — see where you stand first. No sign-up to start.
You apply on the employer's site, with no Olive account needed.
Watch jobs like this. New roles like this one near Menlo Park, CA, by email.
Don't just apply. Show up ready.
Olive works from this exact posting.
At a glance
Olive lists jobs from US employers, including remote roles you can work from the United States.
Job overview
Meta’s Monetization organization develops machine-learning technologies for ads ranking and other large-scale platforms. The Research Scientist will build scalable classifiers and tools, adapt machine-learning methods for parallel environments, and contribute to research, technical demonstrations, publications, and product development. The role collaborates with cross-functional partners and requires deep-learning experience; a PhD and bachelor’s degree may be in progress but must be completed before joining.
Skills & qualifications
Skills
Qualifications
Full job description
Summary:
From making valuable connections between people and businesses to building premium services that deliver high-value experiences, the Monetization organization at Meta empowers people and businesses to succeed in the global economy. As Meta focuses on building the next evolution of social experiences, the Monetization team plays a crucial role in shaping the communication pathways and financial tools that all sized businesses need to thrive in the new digital economic environment. As a Machine Learning Research Scientist on the Monetization team at Meta, you can help build ML/AI technologies that connect users with businesses You’ll help develop solutions that power large-scale platforms and AI innovations to power the Ads-ranking for Meta-scale across all the Meta surfaces.
Required Skills:
Research Scientist, Machine Learning for Monetization (PhD) Responsibilities:
-
Develop highly scalable classifiers and tools leveraging Machine Learning, data regression, and rules based models
-
Suggest, collect, and synthesize requirements to create an effective feature roadmap
-
Adapt standard Machine Learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)
-
Lead and contribute to research that results in tech demos and/or publications
-
Collaborate closely with cross-functional partners and contribute towards Meta's research product development
Minimum Qualifications:
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
-
Currently has, or is in the process of obtaining, a PhD degree in Machine Learning, Artificial Intelligence, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
-
Experience in Deep Learning algorithms and techniques, e.g., convolutional neural networks (CNN), transformers, quantization, data efficient learning, or similar
Preferred Qualifications:
Preferred Qualifications:
-
Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, AAAI, or similar
-
Experience on Data Efficient Learning, domain adaptation, Semi-supervised Learning, etc
-
Experience working and communicating cross-functionally in a team environment
-
Exposure to architectural patterns of large scale software applications
-
Experience solving complex problems and comparing alternative solutions, tradeoffs, and varied points of view to determine a path forward
-
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 manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
Public Compensation:
$122,000/year to $181,000/year + bonus + equity + benefits
Industry: Internet
Equal Opportunity:
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 [email protected].
How this job compares
Set against the 2,164 open Research Scientist jobs on Olive Jobs, counted November 3, 2026.
- Pay
- This posting$122–181K/yr
- California median$183–273K/yr498 salary ranges
- US median$148–225K/yr1,445 salary ranges
This range's midpoint, $152K, is 33% below the California median midpoint ($226K) — in the lowest quarter of Research Scientist salary ranges in California.
- Openings
- Olive Jobs lists 721 open Research Scientist jobs in California and 2,164 across the US. 3% of them nationwide are listed as remote or flexible.
- Experience
- Research Scientist postings that state a minimum ask for 4 years of experience at the median; the middle half ask for 2 to 6 years (1,145 postings).
- Education
- 1,108 of the 2,164 open Research Scientist jobs (51%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 3, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
Prepare for this role
You've read the whole posting — now see how you match it.

