Accertify is looking to solve complex challenges in a high-performance production setting by implementing and delivering high-impact machine learning solutions that push the boundaries of what’s possible, maximizing revenues and user experience while minimizing loss and customer friction.
Requirements
- Knowledge of multiple programming languages, ideally including Python and Java
- Strong big data processing skills using both relational and NoSQL databases
- Experience working as a part of a larger engineering team, documenting code, performing peer code reviews, writing unit tests, and following an SDLC
- High-volume transactional environment experience
- Experience deploying ML models in production and familiarity with MLOps
- Understanding of statistics and machine learning concepts such as traditional and generative ML algorithms; data drift, concept drift, and model decay; model evaluation and validation
- Expertise in Spark and/or Scala
Responsibilities
- Design, develop, test, deploy, and maintain scalable, secure software for batch and real-time ML pipelines in a high-throughput and low-latency production environment
- Optimize pipelines to be distributed, parallel, and/or multi-threaded
- Collaborate with cross-functional teams to troubleshoot and optimize data pipelines
- Demonstrate subject matter expertise and ownership for your team’s services
- Present results to stakeholders and executives as needed
- Collaborate with the Data Science, Big Data, and DevOps teams
- Elevate team performance through mentoring, training, code reviews, and unit testing
Other
- Bachelor's degree in computer science or equivalent
- 4+ years of experience in software engineering in an enterprise setting
- Employment eligibility to work in the U.S. is required, as Accertify will not pursue Visa sponsorship for this position
- Comprehensive Health Coverage: Enjoy peace of mind with medical, dental, and vision insurance options tailored to your needs
- Generous Time Off: Recharge with paid time off, holidays, and personal days to maintain a work-life balance
