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About the Team

At GOAT Group, our Authentication Operations team is essential in educating, training and supporting the Authenticators in physical and digital operations. With the partnership of the operations and retail leaders they focus on ensuring we are creating the best-in-class authenticators by providing them the tools and training they need to verify every product is accurate and authentic.

In this role you will:

Authenticate Listings
- Review and authenticate designer apparel and footwear listings before they are available for sale
- Remove unsafe listings or listings that do not meet marketplace standards
- Ensure listings are accurately described (size, condition, accessories, colorway, release information) and categorized correctly
- Identify inconsistencies, manipulated photos, or inaccurate product details during the authentication process
- Respond to community and marketing requests for additional item moderation
- Review authentication defect reports to understand the nature of inauthentic items that passed through the authentication process and support continuous improvement efforts
Train and Develop Authentication Skills
- Stay up to date on designer authentication methods, release trends, and evolving counterfeit techniques
  Attend training or mentorship sessions with team leads to increase designer apparel and footwear authentication knowledge
- Host training or mentorship sessions to contribute to team learning and development
- Assist in building and improving authentication resources, guides, and hard checkpoints
Contribute to Company-Wide Initiatives and OKRs
- Understand how authentication work affects defect rate and metrics for the Grails designer authentication team overall
- Recognize how authentication volume impacts SLA and operational metrics for the team overall
- Support process improvement initiatives focused on consistency, quality, and efficiency
- Other duties as assigned

Designer Knowledge
- Knowledge and/or familiarity with various designer brands and categories including, but not limited to:
  - Enfants Riches Deprimes
  - Balenciaga
  - Vetements
  - Stone Island
  - Gallery Dept
  - Paly Hollywood
  - Alexander McQueen
  - Amiri
  - Golden Goose
  - Balmain

We are looking for:

Strong knowledge and interest in designer clothing, culture, and trends
Ability to learn/adapt quickly with proven independent problem-solving skills
Strong attention to detail and consistency in decision-making
Enthusiastic about Grailed and/or a power user of the Grailed platform
Professional: Impeccable judgment when trusted with sensitive, non-public data and information
Exhibit Grailed Values: Ownership, Empathetic Approach, Continuous Improvement, Solutions Focus, and Community Driven

Your Performance Will Be Measured On:

How accurately and efficiently you can authenticate designer listings
Consistency in identifying authentic and inauthentic items
Contribution to team knowledge sharing and process improvement initiatives

Requirements:

Work eligibility
Background knowledge about designer footwear and apparel; you bring expertise to the team
Availability to work weekends and holidays (as scheduled)
Availability to work 20–30 hours per week
Availability to attend team meetings and collaborate frequently

GOAT Group represents the leading platforms for authentic sneakers, apparel and accessories. Operating four distinct brands–GOAT, Flight Club, Grailed and alias–GOAT Group has a global community of more than 60 million members across 170 countries.

Founded in 2013, Grailed is the leading community-driven marketplace for rare luxury, streetwear and vintage fashion. The marketplace was built for enthusiasts, by enthusiasts, and features products from brands including Supreme, Raf Simons, Gucci, Saint Laurent, Balenciaga, Prada and more. With a highly curated selection of resale pieces including inventory exclusive to the platform, Grailed makes fashion accessible.

The company is backed by strategic investor Foot Locker, Inc. as well as some of the leading names in venture capital including Park West Asset Management, T. Rowe Price Associates, Inc., Franklin Templeton, Adage Capital Management, Ulysses Management, D1 Capital Partners, Accel, Andreessen Horowitz, Index Ventures, Matrix Partners, Upfront Ventures, Webb Investment Network and Y Combinator.

GOAT Group will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance, if applicable. By applying, you authorize GOAT Group to send you text messages regarding your job application, interview and/or onboarding process, and other job opportunities at GOAT Group. If you are a California resident, please review our California Privacy Rights Notice for Job Applicants. If you are an EU or UK resident, please review our EU / UK Candidate & Employee Privacy Notice.

1a:T2d50,

About the Team

In this role you will:

Authenticate Listings
- Review and authenticate designer apparel and footwear listings before they are available for sale
- Remove unsafe listings or listings that do not meet marketplace standards
- Ensure listings are accurately described (size, condition, accessories, colorway, release information) and categorized correctly
- Identify inconsistencies, manipulated photos, or inaccurate product details during the authentication process
- Respond to community and marketing requests for additional item moderation
- Review authentication defect reports to understand the nature of inauthentic items that passed through the authentication process and support continuous improvement efforts
Train and Develop Authentication Skills
- Stay up to date on designer authentication methods, release trends, and evolving counterfeit techniques
  Attend training or mentorship sessions with team leads to increase designer apparel and footwear authentication knowledge
- Host training or mentorship sessions to contribute to team learning and development
- Assist in building and improving authentication resources, guides, and hard checkpoints
Contribute to Company-Wide Initiatives and OKRs
- Understand how authentication work affects defect rate and metrics for the Grails designer authentication team overall
- Recognize how authentication volume impacts SLA and operational metrics for the team overall
- Support process improvement initiatives focused on consistency, quality, and efficiency
- Other duties as assigned

Designer Knowledge
- Knowledge and/or familiarity with various designer brands and categories including, but not limited to:
  - Enfants Riches Deprimes
  - Balenciaga
  - Vetements
  - Stone Island
  - Gallery Dept
  - Paly Hollywood
  - Alexander McQueen
  - Amiri
  - Golden Goose
  - Balmain

We are looking for:

Strong knowledge and interest in designer clothing, culture, and trends
Ability to learn/adapt quickly with proven independent problem-solving skills
Strong attention to detail and consistency in decision-making
Enthusiastic about Grailed and/or a power user of the Grailed platform
Professional: Impeccable judgment when trusted with sensitive, non-public data and information
Exhibit Grailed Values: Ownership, Empathetic Approach, Continuous Improvement, Solutions Focus, and Community Driven

Your Performance Will Be Measured On:

How accurately and efficiently you can authenticate designer listings
Consistency in identifying authentic and inauthentic items
Contribution to team knowledge sharing and process improvement initiatives

Requirements:

Work eligibility
Background knowledge about designer footwear and apparel; you bring expertise to the team
Availability to work weekends and holidays (as scheduled)
Availability to work 20–30 hours per week
Availability to attend team meetings and collaborate frequently

The hiring range for this position is below, plus benefits (401K, paid time off, dental, medical, vision, disability, life insurance options). To determine starting pay within the hiring range, we carefully consider a variety of factors, including primary work location, role/level, a candidate’s skills, experience, market demands, and internal parity. You may reach out to a recruiter for additional information.

Hiring Range:

$21—$21 USD

1b:T29d3,

Grailed is looking for a Senior Data Engineer to help us build and scale the data infrastructure that powers one of the world's leading fashion resale marketplaces. Our data sits at the center of a complex, peer-to-peer marketplace and touches nearly every part of the business.

This is a hands-on role for a seasoned engineer who takes pride in reliable, well-crafted systems, and who is energized by working closely with a tight-knit team of data partners, engineers, Product Managers, Marketers, and executive leadership who depend on the data every day to make decisions and build great products.

The strongest candidates will have enough breadth of experience across different roles and environments to know that building it right matters as much as building it at all.

What You'll Do

Own the reliability, availability, and accuracy of our data infrastructure, ensuring compliance with data privacy standards
Build, maintain, and improve our data pipeline using our modern data stack (Snowflake, DBT, Airflow, Looker)
Build centralized, durable, and reusable data models that serve the broader business, built with AI and ML consumption in mind
Build and maintain a semantic layer with canonical dimension and metric definitions
Partner closely with Analysts, PMs, Engineers, Marketing, Legal, Fraud, and other stakeholders, translating business needs into actionable data solutions
Build Reverse ETL pipelines in Python; use and build APIs to move and expose data
Proactively bring in new data sources, improve existing data models, and establish SLAs/SLOs for key business dependencies
Champion data governance and help elevate the organization's data maturity — establishing standards, closing gaps, and ensuring data is handled responsibly at every layer
Own data feeds that support in-product marketing, retention communications, and Growth Marketing feeds (i.e. Google Shopping, Meta, Tiktok, etc)

Technical Requirements

5+ years of engineering experience, with a strong foundation in software and data engineering, and familiarity with analytics engineering
Experience with our stack: Snowflake, DBT, Airflow, Fivetran, Segment, Looker, Amplitude, Algolia, AWS/Lambda, Git
Deep experience building, maintaining, and architecting data pipelines end-to-end, ingestion through consumption
Strong SQL skills and proficiency in Python
Experience building and consuming APIs

What We're Looking For

Has driven projects from scoping through delivery, owning the outcomes and not just the tasks, comfortable sitting with ambiguity but driven to resolve it
Treats data quality and observability as first-class concerns, comfortable implementing monitoring and alerting practices that catch issues before the business does
Builds with the team in mind, systems that are intuitive, approachable, and easy for others to understand, extend, and maintain
Pragmatic about technology choices, the goal is solving business problems, not chasing the latest tools
Comfortable operating with a high degree of autonomy, self-directed and able to drive work forward, while keeping the team informed and aligned along the way
Strong communicator, equally effective with engineers and non-technical stakeholders
Naturally elevates the data literacy of those around them by educating and guiding stakeholders toward better data practices

Nice To Have

Familiarity with ML/data science workflows and how data engineering supports them
Exposure to search and discovery platforms
Prior experience in retail, resale, or marketplace commerce, genuine curiosity about the domain a must regardless

One last thing: add a quick note at the bottom of your resume (1-3 lines): what drew you to Grailed and this role, and a recent buying or selling experience on any peer-to-peer marketplace and what made it stand out or fall flat. There are no wrong answers, we actually read all of these.

GOAT Group uses geographic pay tiers based on the employee’s home state to align compensation with market differences across the U.S.

Hiring Range:
Tier 1 (Includes states such as California, New York (including New York City), Washington, Illinois and other higher-cost markets)
$128,000 - $160,000 USD

Tier 2 - (Includes mid-cost markets across the U.S.)
$115,200 - $144,000 USD

Tier 3 - (All other U.S. locations)
$108,800 - $136,000 USD

Hiring Range:

$108,800—$160,000 USD

1c:T2ae8,

ROLE OVERVIEW

Grailed is looking for a Staff Machine Learning Engineer to help us build the models and systems that connect buyers to the inventory they're looking for — and surface things they didn't know they wanted. Our data sits at the center of a complex peer-to-peer marketplace, and the ML layer is what turns a decade of behavioral signals into better search, smarter recommendations, and a marketplace that gets sharper over time.

This is a hands-on technical role for an engineer who takes end-to-end ownership seriously — from architecture through production operation — and who is energized by working on a small, focused team where the infrastructure is still being built and the decisions made now have lasting consequences.

The strongest candidates will bring production instincts alongside technical depth: the kind of engineer who isn't done when the model trains, and who treats monitoring, retraining, and reliability as part of the job, not a follow-on task.

What You'll Do

Own the full lifecycle of predictive models in production — architecture, training pipelines, inference infrastructure, deployment, and ongoing model health
Build and operate the systems that route model outputs into live product surfaces: search ranking, recommendations, feed ordering, and related user-facing experiences
Establish and maintain model monitoring, alerting, drift detection, and retraining cadences — the feedback loops that keep deployed models accurate over time
Partner closely with Data Science, Data Engineering, Product Management, and backend engineering to move work from validated approach to production system
Own the decision-making process on whether to leverage ML infrastructure & expertise from our parent company, GOAT Group, and when to advocate for building in-house solutions.
Contribute to ML infrastructure decisions — serving architecture, feature computation, pipeline orchestration — with an eye toward what scales as the team and model count grows
Set technical standards and raise the bar for how ML systems are built, evaluated, and operated across the pod

Technical Requirements

7+ years of engineering experience, with substantial depth in production machine learning systems.
Demonstrated end-to-end ownership: training pipelines through deployed inference, not just modeling.
Advanced knowledge of ML, AI and statistical models, as well their application in e-commerce settings.
Strong proficiency in Python; SQL; DBT; airflow or similar.
Solid software engineering fundamentals.
Experience with ranking, retrieval, or recommendation systems.
Demonstrated expertise with ML lifecycle tooling — experiment tracking, model versioning, pipeline orchestration, drift detection — and comfort working with modern data infrastructure (cloud warehouse, search/retrieval systems).

What We're Looking For

Takes ownership of developing repeatable end-to-end processes, not just outcomes
Evaluates technical approaches against production constraints — latency, reliability, retraining cost — not just offline metrics
Brings judgment to architecture decisions: knows when to reach for a complex approach and when a simpler one is the right call
Treats model health as a permanent responsibility, not a launch milestone
Communicates clearly with non-technical partners — can translate model behavior, tradeoffs, and timelines into terms that product and business stakeholders can act on
A willing collaborator who keeps people informed and works through ambiguity without going quiet
Genuine curiosity about the domain — fashion, resale, taste — and the specific ML problems it creates

Nice To Have

Experience with semantic enrichment, NLP, or multi-modal ML in a production context
Genuine curiosity about the domain — fashion, resale, style — and the specific ML problems it creates

One last thing — add a quick note at the bottom of your resume (1–3 lines): what drew you to Grailed and this role, and a recent buying or selling experience on any marketplace and what made it stand out or fall flat. There are no wrong answers — we actually read all of these.

GOAT Group uses geographic pay tiers based on the employee’s home state to align compensation with market differences across the U.S.

Hiring Range:
Tier 1 (Includes states such as California, New York (including New York City), Washington, Illinois and other higher-cost markets)
$187,100 - $233,800 USD

Tier 2 - (Includes mid-cost markets across the U.S.)
$168,500 - $210,600 USD

Tier 3 - (All other U.S. locations)
$159,100 - $198,800 USD

Hiring Range:

$159,040—$233,800 USD

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Company jobs
Role	Company	Location	Season	Posted
Digital Authentication Associate	Grailed	Canada	—	11 days ago
Digital Authentication Associate	Grailed	United StatesRemote	—	11 days ago
Senior Data Engineer	Grailed	Los Angeles, CA, United States	—	1 month ago
Staff Machine Learning Engineer	Grailed	United StatesRemote	—	1 month ago