Machine Learning Architect

Machine Learning Architect

The role

The ML Solutions Architect may also provide technical recommendations and contribute to strategic decisions for solutions that do not fall under their purview. The SA will manage applications hosted in multiple technologies and languages such as AWS Sagemeker, H20, Python, Pandas, R and Jupyter Notebooks and should have related relevant experience.

Your responsibilities

  • Work with stakeholders to define requirements constraints, and goals
  • Stay current on changes within the industry and communicate any alignment with bank initiatives with interested parties
  • Understand and adopt all relevant policies, standards and procedures
  • Make technical presentations to technical and non-technical stakeholders
  • Develop and maintain disaster recovery plans and documentation
  • Serve as AI/ML evangelist to inform and consult organization on related issues
  • Establish standards, procedures, guidelines, and best practices related to AI/ML
  • Lead discussions about short term tactical fixes vs. long term strategic goals
  • Prepare budget proposals and operational expenditure statements, Design, develop, communicate, and lead deployment of ML platforms and application
  • Recommend, schedule, and perform software improvements and upgrades
  • Forecast and manage SDLC using agile methodologies and tooling

The must-have skill sets

  • Minimum 5 years’ experience with financial concepts such as advances, securities and derivatives and with with general programming languages
  • Experience building and maintaining big data and big compute environments
  • Extensive experience with statistical programming languages/frameworks
  • Experience with machine learning libraries and frameworks
  • Experience with message busses, databases, data lakes, and data meshes
  • Strong analytical and statistical skills
  • Extensive experience building applications in a cloud environment
  • Extensive engineering experience working on Linux and Windows servers
  • Extensive experience writing financial models or financial software
  • Extensive experience writing, calibrating, and testing financial models
  • Strong understanding of machine learning techniques (supervised, unsupervised, etc)
  • Linux and Windows systems administration
  • Extensive experience working within an agile/SCRUM environment
  • Experience with strong development practices such as test driven development
  • An ability to adopt new ways of working and embrace new technologies and technique

Equal employment opportunity

Rezilyens is an equal opportunity employer and is dedicated to fostering an inclusive and diverse environment for employees from all walks of life. We hire based on talent and we’re proud of our global perspective.