- 35% Machine Learning or Natural Language Processing Project to improve experience for clients, increase automation and provide cost savings.
- 20% Maintain completed ML/NLP programs. All processes used by clients will be supported and any issues with them will be quickly addressed.
- 20% Research for new ML/NLP project to ensure that we are performing all tasks in the best way possible.
- 15% Communicate project status with business stakeholders and senior managers to set expectations on project completions.
- 5% Holds regular meetings for projects (and reports, if any) to update status and help with any road blocks to ensure quicker deliverables.
- 5% Mentor/train junior machine learning engineers.
- Masters/PhD in machine learning or a related field to come up with the ideal solutions for challenging problems.
- Strong object-oriented programming skills to write good quality code.
- Technical Skills: Python, Deep Learning: Tensorflow 2, Keras or PyTorch, Cloud experience.
- Communication skills for working with Product Developers and other engineers.
- Leadership skills: Leading a project with multiple people.
- Write and design application services needed for other engineering teams to use our processes.
- Project management skills to successfully lead a project.
- Problem solving and analysis to come up with the ideal solutions for challenging problems.
Additional Job Description:
- Determining what machine learning algorithms to use.
- Determining whether machine learning should be used for this use case.
- As a manager/project lead: determine what other engineers in the group will be working on.
Working Relationships with:
- Product/Content Developers/ Project Managers to review requirements weekly.
- Senior Software Engineers to coordinate engineering efforts weekly.
- System engineers as needed.
- Hardware needs/concerns monthly.
- Administrative and project related tasks weekly.
- Legacy code and breadth of proprietary domain knowledge Work on improving legacy code.
- Lack of documentation Add more documentation.
- Working with engineers in other time zones Finding times that work for both time zones, replying promptly to emails, keeping track of project progress in CQ/RPD.
- Working with poor performers Coaching.
- Working with competing priorities for multiple stakeholders Setting up appropriate timelines for each project.