What are the responsibilities and job description for the Senior Machine Learning Engineer position at Executive Talent Solutions?
As the Snr Machine Learning engineer, you will forge the company’s technical vision as well as being instrumental in our engineering development. You will bring a modern and innovative approach to building a Federated Learning solution and Privacy Preserving Technologies. The successful candidate will be a hands-on developer, initially leading the engineering development activities and will be responsible for the shaping our technology approach. . This role is 80-90% build and 10-20% management. As the company grows, the ratio may adjust and evolve.
You will be the primary owner of technology delivery across the entire technology lifecycle. This includes hands on keyboard, coding and building the technology platform and user interface that is a critical component for us. Initially, you will lead the development activities, working as part of a team of for development and delivery. Over time you will build and manage a broader team of employee and contracted architects, engineers and developers that can further the vision for our platforms and user interfaces. You will work closely with our product and marketing teams to oversee the build of innovative products and you will assist our customer success team with customer integration.
Experience/Knowledge/Skills
- A bachelor’s / Master degree level education in a numerate subject, or demonstrable evidence of knowledge of ML mechanics.
- Development/building and maintaining a robust machine learning pipelines into production.
- Complex codebase and using version control tools across a team.
- 3 - 5 years’ experience in Python (inc Polars and Pandas), or another development language such as C, C , Go, Ruby, Java or Perl, with a willingness to learn python.
- Deep learning framework such as pytorch or tensorflow.
- At least 2-years federated learning and privacy preserving approaches.
- Desirable: experience with hadoop, kubernetes or another distributed processing system.
- Knowledge of the requirements of IT in a financial institution desirable