Software Engineer, Whatnot

Core Machine Learning

$205-275k

+Stock Options

AWS
Python
Kafka
Elasticsearch
Redis
Spark
Grafana
Flink
Kinesis
Sagemaker
DynamoDB
Datadog
Mid and Senior level
Denver
Los Angeles
New York
San Francisco Bay Area
Whatnot

Live stream platform & marketplace for collectibles

Open for applications

Whatnot

Live stream platform & marketplace for collectibles

501-1000 employees

B2CMarketplaceToysSocialSocial MediaConsumer Goods

Open for applications

$205-275k

+Stock Options

AWS
Python
Kafka
Elasticsearch
Redis
Spark
Grafana
Flink
Kinesis
Sagemaker
DynamoDB
Datadog
Mid and Senior level
Denver
Los Angeles
New York
San Francisco Bay Area

501-1000 employees

B2CMarketplaceToysSocialSocial MediaConsumer Goods

Company mission

Whatnot missions is to enable anyone to turn their passion into a business and bring people together through commerce.

Role

Who you are

  • As our next Software Engineer, Machine Learning you should have 4+ years of experience
  • Bachelor’s degree in Computer Science, Statistics, Applied Mathematics or a related technical field, or equivalent work experience
  • 3+ years of software engineering experience building and maintaining production systems for consumer-scale loads
  • 1+ years of professional experience developing software in Python
  • Ability to work autonomously and drive initiatives across multiple product areas and communicate findings with leadership and product teams
  • Experience with operational, search, and key-value databases such as PostgreSQL, DynamoDB, Elasticsearch, Redis
  • Firm grasp of visualization tools for monitoring and logging e.g. DataDog, Grafana
  • Familiarity with cloud computing platforms and managed services such as AWS Sagemaker, Lambda, Kinesis, S3, EC2, EKS/ECS, Apache Kafka, Flink
  • Professionalism around collaborating in a remote working environment and well tested, reproducible work
  • Exceptional documentation and communication skills

What the job involves

  • We are looking for intellectually curious, highly motivated individuals to become foundational members of our Core Machine Learning team
  • You will help drive the development of Whatnot’s machine learning operations and work with machine learning engineers across the company to design, develop, and deploy backend infrastructure and services to unlock new use cases and integrate machine learning into new product surfaces
  • The ideal candidate is willing and able to flex into an applied research role to develop models that leverage the components they have built
  • Take a leading role in deploying ML models on business critical surfaces & flows
  • Improve our infrastructure to enable new use cases, i.e. spinning up an ANN-based retrieval stack to unlock RAG or make home feed ranking more scalable
  • Develop scalable machine learning design patterns that make it easy for machine learning scientists and engineers to safely deploy models to production
  • Define and advance our technical approach to scalable machine learning
  • Flex outside your comfort zone to help take on new challenges as they emerge

Our take

The collectible toy market is large, and Whatnot has built a unique social platform that enables sellers to use livestreams to showcase their products and reach more buyers. The company’s focus is on collectible toys, some of which are rare and can cost thousands of dollars, and has also expanded to sports cards.

The idea of Whatnot was led by buyer trends. Instagram's live feature became a popular place for selling toys and trading cards, but of course was not set up to facilitate bidding or handling payments after a sale occurs. Whatnot combines live showcasing with follow-up sale capabilities, thus serving the community in a more novel way than established collectibles market players such as eBay.

The company has grown fast. It was established in 2019 and has already expanded from its original category - Funko Pop figurines - to Pokemon cards, pins, sports cards, and many more. There is still plenty of scope for expanding into new categories, as the company aims to establish itself as the go-to for this large niche, which will be facilitated by the strong levels of funding that Whatnot has raised.

Steph headshot

Steph

Company Specialist at Welcome to the Jungle

Insights

Top investors

Some candidates hear
back within 2 weeks

54% employee growth in 12 months

Company

Employee endorsements

Hard working team

"Everyone here puts in the work. It's refreshing to work on a team where everyone is carrying their weight and lifting each other up. The work ethic..."

Funding (last 2 of 6 rounds)

Jul 2022

$260m

SERIES D

Sep 2021

$150m

SERIES C

Total funding: $484.2m

Company benefits

  • Wellness: Health, dental, vision, and life insurance plans. We also cover some of the cost for your dependents as well.
  • Compensation: Full-time Whatnauts receive equity, a WFH stipend to support your remote workspace and a monthly stipend to dogfood the app.
  • Recharge: Flexible Time Off policy, holiday week off at the end of year, and paid parental leave after 1 year with us.
  • Flexibility: Remote-first work culture. We provide a working environment where you're in charge of your time and schedule.

Company values

  • Always listen to customers
  • Move uncomfortably fast
  • Prioritize impact ruthlessly
  • Own everything and nothing
  • Set crazy goals
  • Provide extreme transparency
  • Optimize for the upside
  • Team over ego
  • Figure it out
  • Deeply understand why
  • Have fun & be nice

Company HQ

Marina del Rey, CA

Leadership

Grant LaFontaine

(Co-Founder & CEO)

Former Product Marketing Manager at Google, Project Manager at Facebook. Also co-founded Kit.

Logan Head

(Co-Founder)

Experience in Engineering, including at Maker's Row, Factr, and Flight Club. Former Senior Product Manager at GOAT.

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