Senior Machine Learning Engineer

Job Description Job Description Role Overview Grailed is looking for a Senior Machine Learning Engineer to drive personalization, recommendation, and product marketplace improvement efforts. This is a high-impact role for an experienced builder who thrives in a lean, high-talent environment. You will join a high-velocity team with significant autonomy in taking products from zero to one. The ideal candidate is able to think like a Grailed user as well as a business owner – understanding how data impacts a fashion-forward user experience and also how it is generated and leveraged – while bringing a strong technical background to the role. Specifically, the role requires an understanding of dimension reduction techniques, predictive modeling (statistical or ML), and other advanced analytic methods for applications such as personalization, inventory valuation and search optimization. This key role will operate at the intersection of Data, Product, Engineering, and Marketing, working crossfunctionally to develop compelling data products to support buyers' progression through the purchase cycle. This role will work with our data in Snowflake, develop models in Python, collaborate with ML engineers to structure data for consumption, and coordinate with Product and business unit leaders to align data product development with business objectives. In this role, you will: Act as a technical lead within the data team to advance our recommendation & search algorithms. You will focus on improving the relevance & quality of inventory impressions that are served to prospective buyers. Develop proprietary AI/ML solutions that reflect our unique marketplace dynamics (peer-to-peer exchange of second hand clothing & accessories that are represented as "one-of-one" listings in the market.) Form a high-level perspective on objectives across departments in the organization and how advanced data methods might solve complex business problems. Be able to autonomously and proactively identify business problems that could benefit from data solutions, whether it be application of existing models or the need for the development of new model(s), and take ideas through all phases, from proposal to alignment to execution Establish best practices for training, development and maintenance of data models. This includes using A/B testing and communicating results to stakeholders. Own the deployment of trained models into production in collaboration with Data or ML Engineers. You will be responsible for ensuring reliable, observable deployment into Snowflake using DBT, integrating with existing data pipelines and platform infrastructure, and maintaining version control of code and configurations via Git. Mine user data to identify opportunities for personalization improvements. This includes defining and tracking KPIs related to personalization effectiveness. Develop and maintain data models in Snowflake to support analytical and reporting needs, providing insights to business stakeholders across various departments. Use Python to create ML models and structure the resulting data into a consumable flow. Develop user-to-user mapping capabilities to enhance personalization. Utilize search technologies (i.e. Algolia, AWS OpenSearch) to enhance product discovery and personalization. Analyze message content to detect potentially fraudulent activities, such as identifying keywords or phrases associated with scams, requests for off-platform transactions, or attempts to phish for personal information. Collaborate with product managers, engineers, designers, and business stakeholders to understand their data needs and provide data-driven solutions. We are looking for: Graduate degree in data science, analytics, mathematics, machine learning, computer science, or related field a plus Demonstrated track record of applying analytical skills in a product or business setting may substitute for formal advanced education. 8+ years of relevant work experience in a data or quantitative role, demonstrated success in a startup, high-growth or faced paced organization Experience in marketplace, e-commerce, or fashion/retail domains preferred Experience with web + App product environment preferred Experience with Marketing analytics a bonus Demonstrated success in nontechnical, crossfunctional partner communication Ability to tell a story with data, explaining complex concepts or results to audiences ranging from C-suite to IC levels History of mentoring or developing teammates Ongoing learning (e.g. relevant certifications; open-source contributions; personal projects; etc.) is a plus and shows initiative Technical Competencies Specific tools are less a requirement in this role than an ability to communicate with stakeholders, understand complex, industry-specific problems, maintain a high, self-motivated velocity and bias for action, and have a desire to contribute to problems big and small. That being said, we expect candidates to have Expert level grasps on SQL, Python and complex mathematical concepts related to recommendation and personalization engines, and bring an ability to effectively use coding agents to build and iterate. Our Data stack additionally contains Looker, Amplitude, DBT, Fivetran and AWS Lambdas, experience in these areas is a plus. Math and Statistics Proven expertise in advanced statistical modeling, causal inference, experiment/test design, and working knowledge of machine learning algorithms. Data Science and Engineering Expert level proficiency in Python for data manipulation, statistical analysis, and model development Practical experience with vector databases and embeddings for tasks like user-to-user or user-to-item mapping, semantic search, or item similarity preferred Experience with Snowflake for SQL and data-warehousing preferred Experience with DBT for building modular, version-controlled data transformations preferred Experience with Git for collaborative code development and review preferred Machine Learning and AI Experience in designing, developing, deploying and optimizing Personalization and Recommendation products at scale Experience building models to assess item/listing quality (as defined by likelihood of sales), classify listings, and use NLP on unstructured text Experience modeling time-series forecasts for market trends, seasonality, demand prediction and other relevant KPIs 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) $157,800 - $197,200 USD Tier 2 - (Includes mid-cost markets across the U.S.) $142,100 - $177,600 USD Tier 3 - (All other U.S. locations) $134,300 - $167,800 USD 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: $134,240—$197,200 USD 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. GOAT is the global platform for the greatest products from the past, present and future. Since its founding in 2015, GOAT has become one of the leading and most trusted sneaker platforms in the world, and has expanded to offer apparel and accessories from select emerging, contemporary and iconic brands. Through its unique positioning between the primary and resale markets, the company offers styles across various time periods on its digital platforms and in its retail locations, while delivering products to over 60 million members across 170 countries. Established in New York City over 15 years ago, Flight Club revolutionized sneaker retail as the original consignment store for rare shoes. Carrying the rarest exclusives and collectible sneakers, Flight Club has evolved from a one-stop sneaker destination, to a cultural hub for sneaker enthusiasts and novices alike. With three brick-and-mortar locations in New York City, Los Angeles and Miami, Flight Club remains the premier source for authentic, rare sneakers. 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. 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