Senior Machine Learning Engineer — Production AI Systems

SNAP, Inc.; Palo Alto (CA); Sur place; USD 178 000 - 313 000; Plein temps

Avantages offerts par ce poste

Paid parental leave

Comprehensive medical coverage

Mental health support

RSU equity

Résumé du poste

Snap Inc. is hiring a Machine Learning Engineer to build and deploy ML models powering Snapchat and related services. You will own the end-to-end lifecycle from data analysis to production deployment, partnering with cross-functional teams to prototype and launch ML-driven features.

The role requires strong ML fundamentals, experience with ML frameworks, and a drive to maintain high code quality while addressing security and performance considerations. Hybrid office presence is preferred.

Qualifications

• Strong understanding of machine learning approaches and algorithms.
• Ability to work independently and prioritize duties.
• Experience collaborating with internal and external partners.
• Ability to solve open, ambiguous problems.
• Mentorship and collaboration skills.
• Aptitude for leveraging AI tools while auditing output for security and performance.
• Adaptability to evolving AI systems and tools.

Responsabilités

• Build and deploy ML models powering core products at scale.
• Apply modern ML techniques to solve large-scale problems.
• Own the full ML lifecycle from data analysis to production deployment.
• Collaborate with cross-functional teams to prototype and launch ML features.
• Maintain code quality, security, and scalable architecture for ML services.

Connaissances

ML algorithms

Prioritization

Collaboration

Ambiguity solving

Mentorship

AI tooling

Learning agility

Formation

Bachelor's degree in a technical field

5+ years ML experience or equivalent

PhD with 1+ year ML experience

Outils

TensorFlow

Caffe2

PyTorch

Spark ML

scikit-learn

Description du poste

Snap Inc. is hiring a Machine Learning Engineer to build and deploy ML models powering Snapchat and related services. You will own the end-to-end lifecycle from data analysis to production deployment, partnering with cross-functional teams to prototype and launch ML-driven features.

The role requires strong ML fundamentals, experience with ML frameworks, and a drive to maintain high code quality while addressing security and performance considerations. Hybrid office presence is preferred.