What You'll Do
- Coordinate with our data science team and product and engineering leadership to identify both the long-term and short-term needs of the ML learning work, especially in the areas of NLP, NN, and CV.
- Building and scaling the machine learning team
- Lead the team in bringing the ML models built by the data science team to production with high scalability, reliability, availability, performance, and cost efficiency.
- Lead the team in continuously improving existing ML models together with the data science team
- Lead the team in building data pipelines to support ML model training and serving
- Lead the team in building a labeling system for supervised model training
- Contribute to our org-wide product ideation in collaboration with other engineering leaders, engineers, researchers, product managers, and SMEs.
- Communicate complex concepts and the results of analyses in a clear and effective manner to technical and non-technical audiences.
- Collaborate with other team members and cross-functionally to share knowledge and discuss initiatives.
Who You Are
- 8+ years working as a professional software developer
- 4+ years working as an engineering manager
- 2+ years working in ML-related areas with a great understanding of machine learning design patterns and best practices and experience in shipping machine learning models into distributed, data-intensive production systems
- You can draw on substantial depth and breadth of management experience to lead and grow a machine learning team.
- You collaborate well with teams with different backgrounds/expertise/functions.
- You have expertise in full product lifecycle; technical designs, project planning, iterative implementation, and successful product launches.
- You care about data-driven development, reliability, and responsible experimentation.
- You understand the application of intermediate principles of data science (machine learning, statistics, computer science, mathematics) to solve technical problems.
- You have expertise in the ML Operations lifecycle; data acquisition, model training, and model deployment.
- You have experience and passion for mentoring and encouraging collaborative teams.
- You have experience in cultivating a strong engineering culture in an agile environment.
Your Background
- M.S. in Computer Science or related field or equivalent experience
- Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, documentation, and operations
Bonus Points For
- 2+ years of experience managing a machine learning team
- Knowledge of security and privacy
- Cloud Infrastructure: AWS, Kubernetes
- Building/maintaining large-scale production services
- Experience developing production ML models
- Background in ML/Stats theory

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