In this role you will:

• Build, deploy, and improve robust machine learning models for product features.

• Design both offline and online experiments to test ML product features, and perform data-driven analysis on the results to find actionable insights.

• Provide input and collaborate closely with the ML Infrastructure team towards the development of technical platforms that power ML systems and engineering infrastructure and operations.

• Mentor ML engineering interns and team members.

• Source and interview diverse talent to build and grow a strong ML engineering team.

An ideal candidate has:

• Experience building production machine learning models and systems: Expertise with the full lifecycle of machine learning algorithms in production, including research, deployment, improvements, and maintenance.

• Ability to translate product intuition into data-driven hypotheses that result in impactful machine learning/engineering solutions.

• Experience leading cross-functional teams on strategic machine learning product initiatives from conception to successful product outcomes.

• Demonstrated ability to collaborate with a diverse set of stakeholders such as researchers, business leaders, domain experts (such as doctors), and product managers to solve complex cross-disciplinary problems.

• Masters with at least 6 years of relevant experience, or BS with at least 8 years of relevant experience.

• In-depth experience with at least one machine learning framework (such as TensorFlow, PyTorch, etc.)