What are the responsibilities and job description for the Manager of Machine Learning position at StaffSource?
The Role
Seeking a Manager of Machine Learning and Applied Science who can bring deep expertise in applied science with a proven record of shipping at scale. We are developing a broad suite of technologies on the edge and cloud that enable the operation of our CV / ML-powered platform, including but not limited to computer vision, search, and pricing systems. As a Machine Learning and Applied Science manager within the Advanced Technologies organization, you will be responsible for leading a team of diverse engineers and scientists to deliver high-impact models and algorithms. You will work closely with Machine Learning Applications, Technical Operations, Platform, Hardware, and Product organizations to define requirements and support deployment of algorithms into production.
The right candidate will have a broad machine learning background that includes having shipped multiple systems to production, as well as prior team leadership experience. You must be able to thrive and succeed in an entrepreneurial environment, working collaboratively in a fast-paced environment with multiple stakeholders. You won’t be afraid to break new technological ground and are more than willing to roll up your sleeves, dig in, and get the job done. If you have a background in machine learning, computer vision, pricing, and are interested in developing systems that go out into the real world, please reach out!
Responsibilities
- Lead the Machine Learning and Applied Science team through strategic roadmaps to support business initiatives with high impact.
- Guide the teams technically, engaging in architecture definition, implementation of best practices, and troubleshooting when needed.
- Mange the team through all phases of machine learning development, from concept and design to deployment and monitoring.
- Stay ahead of state-of-the-art research and industry trends in machine learning, computer vision, pricing algorithms, and related fields.
- Collaborate with other Engineering and Product teams to evaluate requirements and use cases for new systems.
- Invest in the career development of the team members, develop future leaders, and create a culture of cohesion and teamwork.
- Participate in talent acquisition processes to ensure that we have world class engineers across all skill and experience levels.
- Establish metrics to measure the productivity of the team, hold people accountable and identify people issues early.
Requirements and Qualifications
