Base: $50,000 - $120,000 py (gross in usd); bonus/...
Remote
6+ years machine learning engineering experience
Production deployment of scalable ml models
Proficiency in python programming language
Sezzle is seeking a Sr. AI Engineer to design and implement scalable machine learning models that enhance their financial platform. The role emphasizes collaboration, innovation, and leadership within a dynamic remote work environment, offering significant opportunities for career advancement
Job Summary
Sezzle is revolutionizing the shopping experience by blending cutting-edge tech with seamless, interest-free installment plans to financially empower the next generation.
The successful candidate will oversee the design, development, and deployment of machine learning models that power financial platforms including fraud detection and credit risk assessment.
This role requires a leader who blends machine learning development with operations to automate the full lifecycle of ML models while mentoring team members to elevate overall capabilities.
Matching Summary
Match Score: 85
Sezzle is seeking a Sr. AI Engineer to design and implement scalable machine learning models that enhance their financial platform. The role emphasizes collaboration, innovation, and leadership within a dynamic remote work environment, offering significant opportunities for career advancement.
Salary
Base: $50,000 - $120,000 per year (Gross in USD); Bonus/Equity: Not specified; Benefits: Not specified
Skills & Requirements
Must-have
6+ years machine learning engineering experience
Production deployment of scalable ML models
Proficiency in Python programming language
AWS cloud services expertise including SageMaker
Experience with Kubernetes and Docker
Nice-to-have
Golang programming experience
Generative AI solution implementation
Strong technical leadership capabilities
High IQ and high EQ personal traits
Experience with Apache Spark and Kafka
Key Requirements
Bachelor's degree in Computer Science or related field
Minimum 6 years of ML engineering experience
Proven track record of deploying models in production