Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams
Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems
Lead large-scale ML initiatives with the customer in mind
Leverage cloud-based architectures and technologies to deliver optimized ML models at scale
Optimize data pipelines to feed ML models
Use programming languages like Python, Scala, C/C++
Leverage compute technologies such as Dask and RAPIDS
Evangelize best practices in all aspects of the engineering and modeling lifecycles
Help recruit, nurture, and retain top engineering talent

Requirements

Bachelor’s degree
At least 10 years of experience designing and building data-intensive solutions using distributed computing
At least 6 years of experience programming in C, C++, Python, or Scala
At least 3 years of experience with the full ML development lifecycle using modern technology in a business critical setting
Master’s Degree (preferred)
3+ years of experience designing, implementing, and scaling production-ready data pipelines that feed ML models (preferred)
2+ years of experience using Dask, RAPIDS, or in High Performance Computing (preferred)
2+ years of experience with the PyData ecosystem (NumPy, Pandas, and Scikit-learn) (preferred)

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningdata pipelinesdistributed computingPythonScalaCC++DaskRAPIDSPyData

Soft Skills

collaborationleadershiprecruitmentnurturing talentcommunication

Certifications

Bachelor's degreeMaster's degree