The Senior Machine Learning Engineer joins the Inventory team to develop custom machine-learning models that drive product vision and customer impact, improving the shopping experience for buyers and sellers.
Lead the creation of engineering plans to address challenging problems by breaking down complex tasks into manageable components, and identifying/estimating milestones.
Mentor junior team members to help them produce high-quality code and machine learning solutions.
Collaborate with engineering teams to share ideas and discuss model capabilities with product managers.
Implement the latest advancements in machine learning to enhance buyer and seller experiences on Etsy.
Develop, optimize, and deploy large-scale machine learning models to achieve key outcomes.
Lead end-to-end machine learning projects to improve marketplace health and trust for Expedia Group.
Locations (2)
Austin, Texas, United States
Seattle, Washington, United States
Compensation
The total cash range for this position in Austin is $112,000.00 to $156,500.00. Employees in this role have the potential to increase their pay up to $179,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. The total cash range for this position in Seattle is $112,000.00 to $156,500.00. Employees in this role have the potential to increase their pay up to $179,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.
Responsibilities
Own machine learning projects end to end, from understanding the business need and defining the approach through execution, launch, measurement, and iteration.
Develop and improve the Marketplace Health Model system to identify behaviors associated with trust, safety, and marketplace-health risks.
Translate complex marketplace challenges into scalable machine learning and statistical modeling solutions.
Partner closely with product, engineering, operations, trust and safety, and other stakeholders to understand needs and deliver practical solutions.
Stay highly engaged with business outcomes by identifying opportunities where machine learning can create meaningful, measurable impact.
Requirements
Graduate degree in a quantitative field (e.g., Computer Science, Statistics, Machine Learning, Operations Research)