Machine Learning Software Engineer 1
Core
Develop generalizable machine learning tools, libraries, and services to support the transition of data science prototypes to production within a finance and accounting firm.
Role type
Machine Learning Software Engineer (Tooling & Infrastructure)
Builds
Reusable ML libraries, RESTful APIs, and production-ready software components for data science projects.
Domain
Finance, Accounting, Machine Learning Infrastructure
Deliverable
production ML models | infrastructure
Required skills
Python, software engineering, algorithm design, data structures, Linux, Docker, RESTful API development
Preferred skills
C/C++ or Go, cloud computing, distributed systems, CI/CD, machine learning algorithms, data preprocessing
Technologies
Python, Docker, Linux, REST APIs
Responsibilities
Define common problems and identify opportunities in the existing codebase to solve current and future problems; Develop libraries and services to address common requirements for machine learning products; Collaborate with data scientists to get their machine learning models from prototype to production; Champion the use and adoption of Toolkit libraries and services; Support team members' growth through pair programming, code review, and knowledge sharing.
Seniority
Individual Contributor (IC), mid-level