Teams at Quantifind

Design, build, and operate scalable, secure infrastructure using IaC principles. Automate deployments, manage on-prem and cloud fleets, improve observability and performance, and collaborate with cross-functional teams to productionize services and ML modules.

Prototype and productionize machine learning solutions using Python, PySpark, and Spark; design and maintain ETL pipelines; train models (including NLP/LLM methods); implement data science features in a production Scala codebase; collaborate with product and platform teams, run experiments, and support customer-focused POCs and deployments.

Build and maintain Quantifind's Apache Spark batch pipeline and platform services to generate risk signals from diverse data. Design scalable algorithms and data structures, implement ETL pipelines, microservices and REST APIs, deploy on Kubernetes, collaborate with Data Science, DevOps and Product, and ensure robust automated unit and integration testing of distributed systems processing terabytes daily.