Senior Machine Learning Engineer
Skills
Computer ScienceApache SparkArtificial IntelligenceAttention To DetailData ScienceMachine LearningPattern Recognition
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Degree in Computer Science Statistics or a comparable quantitative field
- 4-6+ years of post-undergrad experience in a production-grade ML environment
- Strong foundation in machine learning theory and statistical evaluation
- Experience with supervised and unsupervised learning at scale
- Proven track record of moving ML projects from prototype to high-scale production
- Ability to communicate technical findings to technical and non-technical stakeholders
- Proficiency in Python SQL key ML libraries and Spark
- Outcome-oriented mindset with strong focus on business impact
- Attention to detail is critical in fraud prevention
Nice to have
- Fraud experience
- Fintech experience
- Payments experience
- E-commerce experience
- Well-tested code
- Masters degree
- PhD
Day to day
- Own the end-to-end lifecycle of high-impact machine learning projects from offline experimentation through deployment to production.
- Build and maintain production ML models and offline experimentation frameworks that power fraud detection at scale.
- Partner closely with Product Engineering and Risk teams to translate business needs into robust scalable and scientifically sound ML solutions.
Hiring process
- Start your response to the first application question with the word 'Stochastic'