Machine Learning Engineer

Description

Top 3 Skills
1) Endtoend/full stack software solutions development and deployment of Machine Learning (ML) and Artificial Intelligence (AI) algorithms
2) in depth knowledge of Python, .Net and/or Java
3) deep understanding of data design systems and experience handling large sets of data
Job Description
The ideal candidate is a critical thinker, is passionate about solving mathematical and behavioral problems with data and is excited about working in a fastpaced, innovative and collaborative environment as part of the Product Engineering team.
Work Environment
Agile/Scrum. Open working environment conducive to overall success of organizational goals through team collaboration, commitment, and shared objectives. OT is a business casual environment with flexible working hours.
Qualifications
1. Endtoend/full stack software solutions development and deployment of our Machine Learning (ML) and Artificial Intelligence (AI) algorithms
2. Write, design, code, test, implement, debug, and validate applications; document design decisions and develop modular software components; monitor system performance metrics, and identify potential risks/issues
3. Closely partner with product team on time to value discussions and implementation considerations
4. Provide technical guidance, communicate technical decisions, and mentor developers
5. Partner with Product Engineering and Technology leadership to ensure a consistent technology strategy across teams and products
6. Lead multiple software development initiatives at any given time, serving as an expert for the escalation of complex application design and development issues.
7. Perform regular architecture, application design and code reviews on machine learning projects
8. Working knowledge of production data pipelines supporting modeling techniques and model interchange in production settings
9. Deep understanding of data design systems and experience handling large data sets
10. Ability to articulate complex technical ideas and issues effectively
11. Present project metrics, complex ML and AI concepts to both technical and nontechnical audiences.
12. Work with all levels within the company including executive leadership