Snap Inc.
Manager, Machine Learning Engineering, Content Ranking
Snap Inc., Santa Monica, California, United States
Manager, Machine Learning Engineering, Content Ranking
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Manager, Machine Learning Engineering, Content Ranking
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Snap Inc. Overview
Snap Inc. is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company’s core products are Snapchat, Lens Studio, and Spectacles. Snap Engineering teams build products that reach hundreds of millions of Snapchatters around the world. We move fast, with precision, and always execute with privacy at the forefront. What you’ll do
Lead machine learning engineers to create models which drive value for our users and the company Evaluate the technical tradeoffs of key decisions Perform design and code reviews to raise the technical excellence bar Build robust, lasting, and scalable products Iterate quickly without compromising quality Knowledge, Skills & Abilities
Strong understanding of machine learning approaches and algorithms and their applications to Snap’s products Experience setting the direction for a team whose primary output is online ranking/recommendation models Strong management and mentorship skills Excellent verbal and written communication skills, with high attention to detail Ability to collaborate with internal and external stakeholders at all levels of a company Skilled at managing ambiguous problems Minimum Qualifications
Bachelor’s in a related technical field such as computer science or equivalent years of practical work experience 8+ years of post-Bachelor’s ML industry experience; or a Master’s degree in a technical field + 7+ years of post-grad ML experience; or a PhD in a related technical field + 4+ years of post-grad ML experience 1+ year(s) of experience leading machine learning teams that focus on ranking and/or recommendations Preferred Qualifications
Advanced degree in a related technical field Experience with ML frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks Experience working with distributed systems Experience with machine learning, ranking infrastructures, and system designs Ability to proactively learn new concepts and apply them at work Compensation
In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future. Zone A (CA, WA, NYC): base salary range $229,000-$343,000 annually. Zone B: base salary range $218,000-$326,000 annually. Zone C: base salary range $195,000-$292,000 annually. This position is eligible for equity in the form of RSUs. Equal Opportunity and Benefits
Snap is proud to be an equal opportunity employer and is committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical or mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets. We will consider qualified applicants with criminal histories in a manner consistent with applicable law (e.g., San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring, where applicable). Our Benefits: Snap Inc. has you covered with paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that share in Snap’s long-term success. Default Together policy: Snap expects team members to work in an office 4+ days per week to foster collaboration and culture.
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Join to apply for the
Manager, Machine Learning Engineering, Content Ranking
role at
Snap Inc. Overview
Snap Inc. is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company’s core products are Snapchat, Lens Studio, and Spectacles. Snap Engineering teams build products that reach hundreds of millions of Snapchatters around the world. We move fast, with precision, and always execute with privacy at the forefront. What you’ll do
Lead machine learning engineers to create models which drive value for our users and the company Evaluate the technical tradeoffs of key decisions Perform design and code reviews to raise the technical excellence bar Build robust, lasting, and scalable products Iterate quickly without compromising quality Knowledge, Skills & Abilities
Strong understanding of machine learning approaches and algorithms and their applications to Snap’s products Experience setting the direction for a team whose primary output is online ranking/recommendation models Strong management and mentorship skills Excellent verbal and written communication skills, with high attention to detail Ability to collaborate with internal and external stakeholders at all levels of a company Skilled at managing ambiguous problems Minimum Qualifications
Bachelor’s in a related technical field such as computer science or equivalent years of practical work experience 8+ years of post-Bachelor’s ML industry experience; or a Master’s degree in a technical field + 7+ years of post-grad ML experience; or a PhD in a related technical field + 4+ years of post-grad ML experience 1+ year(s) of experience leading machine learning teams that focus on ranking and/or recommendations Preferred Qualifications
Advanced degree in a related technical field Experience with ML frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks Experience working with distributed systems Experience with machine learning, ranking infrastructures, and system designs Ability to proactively learn new concepts and apply them at work Compensation
In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future. Zone A (CA, WA, NYC): base salary range $229,000-$343,000 annually. Zone B: base salary range $218,000-$326,000 annually. Zone C: base salary range $195,000-$292,000 annually. This position is eligible for equity in the form of RSUs. Equal Opportunity and Benefits
Snap is proud to be an equal opportunity employer and is committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical or mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets. We will consider qualified applicants with criminal histories in a manner consistent with applicable law (e.g., San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring, where applicable). Our Benefits: Snap Inc. has you covered with paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that share in Snap’s long-term success. Default Together policy: Snap expects team members to work in an office 4+ days per week to foster collaboration and culture.
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