Machine Learning Engineer, Level 4

Snap Snap · Consumer · Palo Alto, CA +6

Machine Learning Engineer with 3+ years of experience building and deploying ML models for core products like ranking, recommendations, search, content understanding, or image generation. Owns the full ML lifecycle and partners with cross-functional teams to launch ML-driven features. Experience with ML frameworks and infrastructures is preferred.

What you'd actually do

  1. Build and deploy machine learning models that power core products, serving millions of Snapchatters
  2. Apply modern ML techniques to solve large-scale, real-world problems
  3. Own the full ML lifecycle from data analysis to production deployment
  4. Partner with cross-functional teams to prototype and launch ML-driven features
  5. Utilize AI tools and high velocity engineering workflows to design and ship scalable services while upholding rigorous standards for code correctness, security, and production ready quality code

Skills

Required

  • Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience
  • 3+ years of post-Bachelor’s machine learning experience; or Master’s degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field
  • Strong understanding of machine learning approaches and algorithms
  • Able to prioritize duties and work well on your own
  • Ability to work with both internal and external partners
  • Skilled at solving open ambiguous problems
  • Proficiency in, or a strong aptitude for, leveraging AI tools to streamline development, paired with the critical judgment to audit generated output for architectural integrity, performance bottlenecks, and security risks.

Nice to have

  • Advanced degree in computer science or related field
  • Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks
  • Experience working with machine learning, ranking infrastructures, and system design
  • Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of engineering trends and modern development practices
  • Strong collaboration and mentorship skills

What the JD emphasized

  • Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning

Other signals

  • Build and deploy machine learning models that power core products, serving millions of Snapchatters
  • Apply modern ML techniques to solve large-scale, real-world problems
  • Own the full ML lifecycle from data analysis to production deployment
  • Partner with cross-functional teams to prototype and launch ML-driven features