Principal ML Engineer, Signals & Measurement

SNAP, Inc.; Seattle (WA); On-site; USD 276,000 - 414,000; Full time

Benefits offered by this job

Paid parental leave

Medical coverage

Mental health support

Equity in RSUs

Job summary

Snap Inc. is seeking a Principal Machine Learning Engineer to join the Signals & Measurement team.

You will design and scale ML systems across the signal lifecycle, from acquisition to causal measurement, to support monetization strategies. The role requires leading ML initiatives, collaborating with cross-functional teams, and applying cutting-edge ML techniques while ensuring scalability, availability, and cost management.

Qualifications

• Bachelor's degree in a technical field such as computer science, mathematics, statistics or equivalent years of experience.
• 9+ years of post-Bachelor’s ML experience; or a Master’s degree + 8+ years; or a PhD + 5+ years of post-grad ML experience.
• 2+ years of experience with technical leadership or domain-expert to a technical organization.
• Experience developing and shipping performant and scalable ML models for recommendation or ranking use cases.
• Experience with TensorFlow, PyTorch, or related deep learning frameworks.

Responsibilities

• Design and develop ML systems across the third‑party signal lifecycle, from acquisition to causal measurement.
• Design, implement, and scale ML models to support Snap's monetization strategies.
• Collaborate with cross‑functional teams to align ML strategies with company objectives.
• Stay up‑to‑date with ML advances and apply them to complex problems.
• Provide technical direction influencing the ML community.

Skills

ML concepts

Deep learning

Ranking/Recommendation

Programming skills

Mentorship

Education

Bachelor's in technical field

Tools

TensorFlow

PyTorch

Job description

Snap Inc. is seeking a Principal Machine Learning Engineer to join the Signals & Measurement team.

You will design and scale ML systems across the signal lifecycle, from acquisition to causal measurement, to support monetization strategies. The role requires leading ML initiatives, collaborating with cross-functional teams, and applying cutting-edge ML techniques while ensuring scalability, availability, and cost management.