The Trade Desk
Business Development GM (Holdco)
New York, US•2 months ago
$134K – $245K
business developmentsalesagency
Data Science10 months agoHybrid
AppLovin
Foundational Research Scientist
machine learningdeep learningrecommender systemsPythonPyTorchresearchlarge-scale dataexperimentationonline evaluationacademic-industrial hybrid
Key details
Salary
Not specified
Employment type
Full-time
Seniority
Mid-level
Years experience
5-10
Location
Palo Alto, United States
Full job description
AppLovin is hiring a mid-level full-time research scientist to advance recommender systems using machine learning. The role involves foundational research, leveraging large-scale live user data and compute resources, collaborating with engineering and product teams to deploy models, and publishing research. Candidates must have a PhD or equivalent experience in CS, ML, or related fields, strong deep learning skills, proficiency in Python and PyTorch, and experience with large-scale data and experimentation. Preferred qualifications include publications in top ML venues, knowledge of sequential modeling, representation learning, causal inference, online experimentation, and industry ML deployment experience. Benefits include equity eligibility, comprehensive health insurance, 401(k), unlimited discretionary time off, paid holidays, and sick leave. The position is located in Palo Alto, California. Salary range is $252,000 to $400,000 USD.
What you'll do
- Drive foundational research to create new recommendation models and paradigms
- Leverage rich live user data and large-scale compute to validate models rapidly
- Collaborate closely with engineering and product teams to operationalize research
- Publish findings and contribute to the broader ML and RecSys community
Requirements
- PhD (or equivalent research experience) in CS, ML, Statistics, or related field
- Strong background in deep learning
- Proven track record of research excellence (publications, awards, impactful projects)
- Proficiency in Python and modern ML frameworks (PyTorch)
- Experience with large-scale data and experimentation
- Publications in top venues (NeurIPS, ICML, ICLR, KDD, RecSys, SIGIR, WWW) - nice to have
- Experience with sequential modeling, representation learning, or causal inference - nice to have
- Knowledge of online experimentation and evaluation methodologies - nice to have
- Industry experience deploying ML in production systems - nice to have
Tech stack
PythonPyTorchmachine learningdeep learning
Benefits
Equity eligibleMedical, Dental, Vision, Life, Disability insurance401(k) Retirement PlanUnlimited Discretionary Time Off10 paid holidays per year80 hours paid sick leave per year
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