Sr. Staff Machine Learning Engineer, Closeup Relevance
Sr. Staff Machine Learning Engineer, Closeup Relevance
Job Description
Responsibilities
- Work in a cross-team environment with talented ML engineers on state-of-the-art recommendation tech stack and lead innovation or redesign of the full recommendation funnel
- Lead ML innovations with impact across the organization
- Work closely with engineering teams such as ATG, ML Platform, Closeup Product, Content Quality and Core Infrastructure to bring superior Closeup experience to users
- Develop an inspiring technical vision and ambitious but grounded strategy for the team and deliver outstanding results
- Provide visibility for senior leadership into the team’s global impact
- Partner with stakeholders including product management and data scientists to expand impact across the company
- Mentor and grow senior engineers on the team
- Build a culture of innovations and excellence
Qualifications
- 7+ years of professional experience in Machine Learning
- 5+ years of proposing and delivering innovations from original research or adopting cutting edge ML research
- 3+ years of experience in leading large-scale and mature ML recommendation systems teams, in an end-to-end fashion
- Bachelor’s/Master’s degree in a relevant field such as computer science, or equivalent experience
- Thrives in ambiguity, skilled in defining and exploring open ended problems
- Experience in setting and delivering technical directions at both team and organizational level
- Expertise in machine learning modeling and infrastructure
- Adept in statistics, backend, batch and realtime processing systems
- Ability to drive the team roadmap end to end
- A knack for product and impact on users of a consumer product
Locations
- Palo Alto, CA; Seattle, WA, US
Salary
268,084 - 469,147 USD / yearly
Estimated Salary Rangemedium confidence
300,000 - 500,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Machine Learning modeling and infrastructureintermediate
- Statisticsintermediate
- Backend systemsintermediate
- Batch processing systemsintermediate
- Realtime processing systemsintermediate
- Leading large-scale ML recommendation systemsintermediate
- Proposing and delivering ML innovations from researchintermediate
Required Qualifications
- 7+ years of professional experience in Machine Learning (experience)
- 5+ years of proposing and delivering innovations from original research or adopting cutting edge ML research (experience)
- 3+ years of experience in leading large-scale and mature ML recommendation systems teams, in an end-to-end fashion (experience)
- Bachelor’s/Master’s degree in a relevant field such as computer science, or equivalent experience (experience)
- Thrives in ambiguity, skilled in defining and exploring open ended problems (experience)
- Experience in setting and delivering technical directions at both team and organizational level (experience)
- Expertise in machine learning modeling and infrastructure (experience)
- Adept in statistics, backend, batch and realtime processing systems (experience)
- Ability to drive the team roadmap end to end (experience)
- A knack for product and impact on users of a consumer product (experience)
Responsibilities
- Work in a cross-team environment with talented ML engineers on state-of-the-art recommendation tech stack and lead innovation or redesign of the full recommendation funnel
- Lead ML innovations with impact across the organization
- Work closely with engineering teams such as ATG, ML Platform, Closeup Product, Content Quality and Core Infrastructure to bring superior Closeup experience to users
- Develop an inspiring technical vision and ambitious but grounded strategy for the team and deliver outstanding results
- Provide visibility for senior leadership into the team’s global impact
- Partner with stakeholders including product management and data scientists to expand impact across the company
- Mentor and grow senior engineers on the team
- Build a culture of innovations and excellence
Tags & Categories
Sr. Staff Machine Learning Engineer, Closeup Relevance
Sr. Staff Machine Learning Engineer, Closeup Relevance
Job Description
Responsibilities
- Work in a cross-team environment with talented ML engineers on state-of-the-art recommendation tech stack and lead innovation or redesign of the full recommendation funnel
- Lead ML innovations with impact across the organization
- Work closely with engineering teams such as ATG, ML Platform, Closeup Product, Content Quality and Core Infrastructure to bring superior Closeup experience to users
- Develop an inspiring technical vision and ambitious but grounded strategy for the team and deliver outstanding results
- Provide visibility for senior leadership into the team’s global impact
- Partner with stakeholders including product management and data scientists to expand impact across the company
- Mentor and grow senior engineers on the team
- Build a culture of innovations and excellence
Qualifications
- 7+ years of professional experience in Machine Learning
- 5+ years of proposing and delivering innovations from original research or adopting cutting edge ML research
- 3+ years of experience in leading large-scale and mature ML recommendation systems teams, in an end-to-end fashion
- Bachelor’s/Master’s degree in a relevant field such as computer science, or equivalent experience
- Thrives in ambiguity, skilled in defining and exploring open ended problems
- Experience in setting and delivering technical directions at both team and organizational level
- Expertise in machine learning modeling and infrastructure
- Adept in statistics, backend, batch and realtime processing systems
- Ability to drive the team roadmap end to end
- A knack for product and impact on users of a consumer product
Locations
- Palo Alto, CA; Seattle, WA, US
Salary
268,084 - 469,147 USD / yearly
Estimated Salary Rangemedium confidence
300,000 - 500,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Machine Learning modeling and infrastructureintermediate
- Statisticsintermediate
- Backend systemsintermediate
- Batch processing systemsintermediate
- Realtime processing systemsintermediate
- Leading large-scale ML recommendation systemsintermediate
- Proposing and delivering ML innovations from researchintermediate
Required Qualifications
- 7+ years of professional experience in Machine Learning (experience)
- 5+ years of proposing and delivering innovations from original research or adopting cutting edge ML research (experience)
- 3+ years of experience in leading large-scale and mature ML recommendation systems teams, in an end-to-end fashion (experience)
- Bachelor’s/Master’s degree in a relevant field such as computer science, or equivalent experience (experience)
- Thrives in ambiguity, skilled in defining and exploring open ended problems (experience)
- Experience in setting and delivering technical directions at both team and organizational level (experience)
- Expertise in machine learning modeling and infrastructure (experience)
- Adept in statistics, backend, batch and realtime processing systems (experience)
- Ability to drive the team roadmap end to end (experience)
- A knack for product and impact on users of a consumer product (experience)
Responsibilities
- Work in a cross-team environment with talented ML engineers on state-of-the-art recommendation tech stack and lead innovation or redesign of the full recommendation funnel
- Lead ML innovations with impact across the organization
- Work closely with engineering teams such as ATG, ML Platform, Closeup Product, Content Quality and Core Infrastructure to bring superior Closeup experience to users
- Develop an inspiring technical vision and ambitious but grounded strategy for the team and deliver outstanding results
- Provide visibility for senior leadership into the team’s global impact
- Partner with stakeholders including product management and data scientists to expand impact across the company
- Mentor and grow senior engineers on the team
- Build a culture of innovations and excellence
Tags & Categories