Base: $50,000 - $120,000 py (gross in usd); bonus/...
Remote
6+ years machine learning engineering experience
Python proficiency required
Aws cloud services expertise
Sezzle is seeking a Sr. AI Engineer to design, develop, and deploy machine learning models that enhance its financial platform, focusing on personalized recommendations and fraud detection. This remote position offers significant career advancement opportunities within a dynamic and innovative team dedicated to transforming the shopping experience
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 role involves overseeing the design, development, and deployment of machine learning models that power financial platforms including fraud detection and credit risk assessment.
Candidates must demonstrate relentlessly high standards, a willingness to challenge decisions, and a focus on delivering results in a fast-paced environment.
Matching Summary
Match Score: 85
Sezzle is seeking a Sr. AI Engineer to design, develop, and deploy machine learning models that enhance its financial platform, focusing on personalized recommendations and fraud detection. This remote position offers significant career advancement opportunities within a dynamic and innovative team dedicated to transforming the shopping experience.
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
Python proficiency required
AWS cloud services expertise
Production ML model deployment
MLOps lifecycle management
Nice-to-have
Golang programming experience
Kubernetes and Docker knowledge
Generative AI solutions implementation
High EQ and leadership skills
Apache Spark and Kafka familiarity
Key Requirements
Bachelor's degree in Computer Science or related field
Minimum 6 years of ML engineering experience
Proven track record of deploying scalable ML models