Manager, Machine Learning Engineering, Web Ads Ranking

Snap Inc.; Los Angeles (CA); On-site; USD 229,000 - 343,000; Full time

Benefits offered by this job

Paid parental leave

Comprehensive medical coverage

Emotional and mental health support programs

Compensation packages with equity

Job summary

Snap Inc. is seeking a seasoned leader to guide a team of machine learning and software engineers in developing large-scale indexing and ranking systems for Snapchat ads. This role involves collaboration with product teams to define architecture and vision while nurturing a high-performing team by upholding standards of engineering and machine learning excellence.

The ideal candidate will have significant industry experience and a strong understanding of machine learning, recommendation systems, and the ability to manage and solve complex challenges dynamically.

Qualifications

• 8+ years of post-Bachelor’s ML industry experience; or a Master’s degree and 7+ years; or a PhD and 4+ years.
• 1+ years of experience leading machine learning teams focusing on ranking or recommendations.
• Experience with real-time recommendation or search ranking systems is preferred.

Responsibilities

• Lead a team of engineers to build large-scale indexing, retrieval, and ranking systems.
• Collaborate with product teams to define system architecture and vision.
• Build evaluation frameworks for rapid iteration and high-quality decision-making.

Skills

Machine Learning approaches

Large language models

Management and mentorship

Communication skills

Problem-solving

Education

Bachelor’s in a related technical field

Tools

TensorFlow

PyTorch

Spark ML

Job description

What you’ll do:

• Lead a team of machine learning engineers and software engineers to build large-scale indexing, retrieval, and ranking systems that deliver the most relevant Snapchat ads and drive revenue
• Collaborate with broad product teams in Snap to define the architecture and vision of the system, and grow the team beyond the initial scope
• Build the evaluation framework that enables rapid iteration and high-quality decision-making, working closely with Data Science and Product partners to define success metrics and measure outcomes
• Build and grow a high-performing team by raising the bar for engineering and ML excellence, developing talent, and helping shape Snap’s broader machine learning strategy

Knowledge, Skills & Abilities:

• Deep understanding of machine learning approaches, algorithms and their application to recommender, ads and search system
• Experience on utilizing large language models for tasks like keyword extraction, description generation, and semantic relevance judging
• Strong management and mentorship skills, fostering a collaborative and innovative team culture
• Excellent verbal and written communication skills, with meticulous attention to detail
• Ability to effectively collaborate with stakeholders at all levels, both internally and externally
• Proficiency in managing and solving ambiguous problems

Minimum Qualifications:

• Bachelor’s in a related technical field such as computer science or equivalent years of experience
• 8+ years of post-Bachelor’s ML industry experience; or a Master’s degree in a technical field + 7+ year 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 teams that focus on ranking or recommendations

Preferred Qualifications:

• Experience with real-time recommendation or search ranking systems
• Experience with building LLM based information retrieval or tagging system
• Experience working with distributed systems
• Experience working with machine learning, ranking infrastructures, and system designs
• Ability to proactively learn new concepts and apply them at work
• Experience working with large-scale machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks

Accommodations and Disability Policy:

If you have a disability or special need that requires accommodation, please don’t be shy and provide us some information (https://docs.google.com/forms/d/e/1FAIpQLScV7t31iR3yYR9ztGDHJpbvL63svWpb6s0afkBkLEjGnDx4Kg/viewform).

Benefits:

Our Benefits (https://careers.snap.com/benefits) : Snap Inc. is its own community, so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap’s long-term success!

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): The base salary range for this position is $229,000-$343,000 annually.

Zone B: The base salary range for this position is $218,000-$326,000 annually.

Zone C: The base salary range for this position is $195,000-$292,000 annually.

This position is eligible for equity in the form of RSUs.

EEO Statement:

Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, 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 are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable).