Snap
Machine Learning Engineer, Causal Inference, Level 5
Los Angeles, California · Senior
Stay score
odds of building a lasting career here
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
This range already reaches Level IV — the maximum four lottery entries.
DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · Los Angeles-Long Beach-Anaheim, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
Employer immigration record
from this employer's Department of Labor filings
Green-card filing pattern in this occupation
Green-card follow-through: 96%
Files H-1B transfers
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
Community outcomes
No reports yet — be the first to help the next applicant.
About the role
- We believe the camera presents the greatest opportunity to improve the way people live and communicate.
- Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.
- We move fast, with precision, and always execute with privacy at the forefront.
Responsibilities
- Design and build models that quantify causal impact, optimize decision-making, and drive value for users, advertisers, and the business
- Design, analyze, and interpret A/B tests and quasi-experiments; collaborate closely with product and engineering partners to shape experimentation strategies
- Conduct code reviews, maintain high engineering standards, and build scalable, maintainable infrastructure
- Strong communication and mentorship skills; able to translate technical insights for non-technical partners
- Snap Inc. is its own community, so we've got your back!
- We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms.
Requirements
- Bachelor's degree in computer science, statistics, economics, or a related technical field, or equivalent practical experience
- Experience designing and analyzing online experiments (A/B tests) and leveraging causal ML in production systems
- Strong understanding of causal inference and modern approaches to estimating treatment effects (e.g., meta learners, propensity score matching, instrumental variables)
Nice to have
- Advanced degree (MS/PhD) in a quantitative field such as statistics, data science, computer science, economics, or operations research
- Experience with causal inference libraries such as CausalML, EconML or DoWhy
- Background in deploying models in production settings and working with ML or experimentation infrastructure
- Deep understanding of experimentation nuances, including intent-to-treat (ITT) vs. ghost ad methodologies, and the trade-offs between frequentist and Bayesian inference for decision-making under uncertainty
- Experience applying causal inference in domains like personalization, ad or marketplace dynamics
- To reflect this, we practice a "default together" approach and expect our team members to work in an office 4+ days per week.
Skills
- Experience with applied data science, including A/B testing, uplift modeling, and experimentation infrastructure
- Proficient in Python and common data/machine learning libraries (e.g., pandas, NumPy, scikit-learn, CausalM etc.)
- Skilled at solving open-ended problems with a mix of statistical thinking and engineering pragmatism
- Comfortable working independently and collaborating across cross-functional teams
Compensation
- In the United States, work locations are assigned a pay zone which determines the salary range for the position.
- The successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions.
- The starting pay may be negotiable within the salary range for the position.
- These pay zones may be modified in the future.
- The base salary range for this position is $209,000-$313,000 annually.
- The base salary range for this position is $199,000-$297,000 annually.
- The base salary range for this position is $178,000-$266,000 annually.
Company info
- We're deeply committed to the well-being of everyone in our global community, which is why our values are at the root of everything we do.
- We're looking for a Machine Learning Engineer to join Snap Inc!
This listing is sourced directly from Snap's careers page and normalized into a canonical job model.