Manager of Machine Learning Engineering, Snap

Content Relevance

$222-333k

+ Eligible for equity in the form of RSUs

Tensorflow
Spark
Scikit-Learn
PyTorch
Senior and Expert level
Los Angeles
San Francisco Bay Area
Snap

Social media & camera company

Be an early applicant

Snap

Social media & camera company

1001+ employees

B2CAugmented RealitySocialSocial MediaMobile

Be an early applicant

$222-333k

+ Eligible for equity in the form of RSUs

Tensorflow
Spark
Scikit-Learn
PyTorch
Senior and Expert level
Los Angeles
San Francisco Bay Area

1001+ employees

B2CAugmented RealitySocialSocial MediaMobile

Company mission

To empower people to express themselves, live in the moment, learn about the world, and have fun together.

Role

Who you are

  • Deep understanding of machine learning approaches, algorithms and their application to recommender system
  • Experience setting the direction for teams focused on developing online ranking and recommendation models
  • 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
  • Bachelor’s in a related technical field such as computer science or equivalent years of experience
  • 8+ years of ML industry experience
  • 2+ years of experience leading machine learning teams teams that focus on ranking and/or recommendations

Desirable

  • Experience with real-time recommendation systems
  • Experience working with large-scale machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks
  • 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

What the job involves

  • We're looking for a Machine Learning Engineering Manager to join the Content Relevance team at Snap!
  • Lead a team of machine learning engineers and software engineers in developing and optimizing our personalized video recommendation engine
  • Define the overall architecture of the content recommender system, ensuring scalability, performance, and reliability
  • Drive rapid iteration without compromising quality: work closely with infrastructure engineers to build robust machine learning infrastructure to support the recommender system
  • Evaluate the technical tradeoffs in key decision-making processes to ensure optimal outcomes: conduct A/B testing and analyze performance metrics to continuously improve the recommender system
  • Perform design and code reviews to raise technical excellence bar

Our take

Snap is the social media giant that owns Snapchat, a social media mobile app released in 2011. Created to serve as a more emotive communication form than texting, the app has gained mass popularity, reaching upwards of 400 million daily users worldwide.

After rejecting a billion dollar acquisition from Meta (then Facebook) in 2013, Snap has found itself in competition with the social media giant, particularly with Instagram. Despite this, the company has marked a place for itself in the ever competitive social media space through developing features like a Discover tab, augmented reality lenses, in-app games, ads and monetisation options, as well as launching its paid service, Snapchat+.

Snap has so far not earned an annual profit since going public in 2017, but as Snapchat's user base has continually increased it has nearly closed the gap. Like other tech companies it suffered in late 2022 due to a surprise drop in advertising revenue, but has been rebuilding to its former trajectory since then. Given Snapchat's lasting popularity amongst young people, further success appears likely.

Kirsty headshot

Kirsty

Company Specialist

Insights

Top investors

Few candidates hear
back within 2 weeks

-9% employee growth in 12 months

Company

Funding (last 2 of 7 rounds)

May 2016

$1.8bn

SERIES F

Mar 2015

$200m

SERIES E

Total funding: $2.6bn

Company benefits

  • Paid maternity, paternity and family caregiver leave
  • Adoption, surrogacy, infertility and fertility preservation benefits
  • Backup child care coverage, caregiver assistance and digital maternity care support
  • Short-term disability, long-term disability, life insurance and AD&D insurance
  • Comprehensive medical coverage, including PPO, HSA and HMO options
  • Dental coverage, including orthodontia benefits
  • Vision coverage, including LASIK benefits
  • Gym perks and discounts
  • Team fitness classes, hikes and races
  • Sports leagues
  • Cooking and nutritional workshops
  • Generous time off and leave programmes
  • Meditation and yoga classes
  • Emotional and mental health support programmes and apps
  • Social gatherings, team outings and volunteering programmes
  • Speaker series, classes and subscriptions to educational programmes
  • Snap Inc. provides a 401(k) plan that allows you to save on a pre-tax, Roth and after-tax basis for your retirement (yes, we even have the Mega Backdoor option!)
  • Rocket Lawyer memberships
  • Financial education programmes
  • Compensation packages that let you share in Snap's long-term success!
  • Have a teammate going through a tough time? Lend them a hand through our internal Snap-a-wish programme! We'll work hard to make sure they get the support they need.

Company values

  • We Are Kind - We solve problems through action, make high-quality decisions and think with a strategic mindset
  • We Are Smart - We solve problems through action, make high-quality decisions and think with a strategic mindset
  • We Are Creative - We gracefully manage ambiguity, cultivate innovation and demonstrate an insatiable desire to learn

Company HQ

Sunset Park, Santa Monica, CA

Leadership

Evan Spiegel

(CEO)

Graduated from Standford with a BS in Product Design.

Bobby Murphy

(CTO)

Studied Mathematical and Computational Science at Stanford.

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