- Play a critical role in setting the direction and goals for a sizable team, in terms of project impact, ML system design, and ML excellence
- Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)
- Re-evaluate the tradeoffs of already shipped features/ML systems, and you are able to drive large efforts across multiple teams to reduce technical debt, designing from first principles when appropriate
- Leading a team from a technical perspective to develop ML best practices and influence engineering culture
- Be a go-to person to escalate the most complex online/production performance and evaluation issues, that require an in depth knowledge of how the machine learning system interacts with systems around it
- Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules based models
- Suggest, collect and synthesize requirements and create effective feature roadmap
- Code deliverables in tandem with the engineering team
- Experience in software engineering, or a relevant field
- Experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical field
- Experience with scripting languages such as Python, Javascript or Hack
- Experience leading major initiatives successfully
- Experience building and shipping high quality work and achieving high reliability
- Experience with developing machine learning models at scale from inception to business impact
- Knowledge developing and debugging in C/C++ and Java, or experience with scripting languages such as Python, Perl, PHP, and/or shell scripts
- Experience demonstrating technical leadership working with teams, owning projects, defining and setting technical direction for projects
- Experienced in utilizing data and analysis to explain technical problems and providing detailed feedback and solutions
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- Masters degree or PhD in Computer Science or a related technical field
- Exposure to architectural patterns of large scale software applications
- Experience with scripting languages such as Pytorch and TF
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