Startops is hiring: Senior Data Scientist / Machine Learning Engineer - Listing
Startops, San Francisco, CA, United States
Senior Data Scientist / Machine Learning Engineer - Listing Quality
Develop and deploy scalable deep learning models to improve listing accuracy and quality
Location: San Francisco, California, United States
Compensation: $192,000 - 264,000 USD / year
Job Tags: Operations
About The Role
Senior Data Scientist / Machine Learning Engineer
Faire is an online wholesale marketplace built on the belief that the future is local — independent retailers around the globe are doing more revenue than Walmart and Amazon combined, but individually, they are small compared to these massive entities. At Faire, we’re using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so that small businesses everywhere can compete with these big box and e-commerce giants.
By supporting the growth of independent businesses, Faire is driving positive economic impact in local communities, globally. We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.
About This Role
Faire leverages the power of machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores. At Faire, the Data Science team is responsible for creating and maintaining a diverse range of algorithms and models that power our marketplace. We are dedicated to building machine learning models that help our customers thrive.
As a member of the Brand Data Science team working on Listing Quality, you will be responsible for improving the quality of product listings to help retailers find and evaluate products on Faire. You will use ML and AI to tackle critical challenges, such as enhancing image and text quality, extracting structured product attributes, and accurately identifying duplicates and product variants. You will leverage deep learning, multi-modal LLMs, and human‑in‑the‑loop training to create high‑performance solutions. This space has been evolving rapidly with advancements in AI and you will be at the forefront of applying the latest technology to drive real‑world impact. You will independently design and implement solutions and work with the cross‑functional Listing Quality pod, including product, design, engineering, analytics, and operations, to solve problems end‑to‑end.
What You’ll Do
Drive data science vision, strategy, and execution on Listing Quality, using ML and AI solutions to improve the quality of Faire’s product listings.
Use deep learning, LLM fine tuning, and human‑in‑the‑loop training to automatically detect and address issues with high accuracy.
Act as a lead on the cross‑functional Listing Quality pod, thinking end‑to‑end about brand and retailer experiences.
Qualifications
3+ years of industry experience using machine learning to solve real‑world problems
Experience with relevant business problems (e.g. e‑commerce)
Experience with relevant technical methods (e.g. LLM fine tuning, deep learning, or human‑in‑the‑loop machine learning)
Strong programming skills
An excitement and willingness to learn new tools and techniques
The ability to design and implement ML solutions without supervision
Strong communication skills and the ability to work in a highly cross‑functional team
Great To Haves
Master’s or PhD in Computer Science, Statistics, or related STEM fields is highly recommended
Previous experience in listing quality for e‑commerce
Previous experience in supervised fine tuning of multi‑modal LLMs
Experience deploying and optimizing LLM inference systems at scale (10B+ tokens), with focus on cost efficiency and product impact
Salary Range
San Francisco: the pay range for this role is $192,000 to $264,000 per year.
This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.
Why You’ll Love Working at Faire
We are entrepreneurs: Faire is being built for entrepreneurs, by entrepreneurs. We believe entrepreneurship is a calling and our mission is to empower entrepreneurs to chase their dreams. Every member of our team is taking part in the founding process.
We are using technology and data to level the playing field: We are leveraging the power of product innovation and machine learning to connect brands and boutiques from all over the world, building a growing community of more than 350,000 small business owners.
We build products our customers love: Everything we do is ultimately in the service of helping our customers grow their business because our goal is to grow the pie — not steal a piece from it. Running a small business is hard work, but using Faire makes it easy.
We are curious and resourceful: Inquisitive by default, we explore every possibility, test every assumption, and develop creative solutions to the challenges at hand. We lead with curiosity and data in our decision making, and reason from a first principles mentality.
Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression.
Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs.
For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire’s Privacy Notice.
#J-18808-Ljbffr
In Summary: Senior Data Scientist / Machine Learning Engineer - Listing Quality - Develop and deploy scalable deep learning models to improve listing accuracy and quality . Faire leverages the power of machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores .
En Español: Científico de datos senior / Ingeniero del aprendizaje automático Faire es un mercado mayorista en línea construido sobre la creencia de que el futuro es local minoristas independientes alrededor del mundo están generando más ingresos que Walmart y Amazon combinados, pero individualmente son pequeños en comparación con estas entidades masivas. En Faire, estamos utilizando el poder de la tecnología, los datos y el aprendizaje automatizado para conectar a esta próspera comunidad de emprendedores de todo el mundo. Si cree en la comunidad, únase a nosotros. About This Role Faire aprovecha el poder del aprendizaje automático y las ideas de datos para revolucionar la industria mayorista, permitiendo que los minoristas locales compitan con gigantes como Amazon y grandes tiendas de boxes. En Faire, el equipo Data Science es responsable de crear y mantener una variedad diversa de algoritmos y modelos que impulsan nuestro mercado. Estamos dedicados a construir modelos de aprendizaje automatizado que ayuden a nuestros clientes a prosperar. Como miembro del equipo Brand Data Science que trabaja en Listing Quality, usted será responsable de mejorar la calidad de las listas de productos para ayudar a los minoristes a encontrar y evaluar productos en Faire. Utilizará ML e IA para abordar desafíos críticos de imagen, tales como aumentar rápidamente la calidad y el texto, extraer atributos estructurados de producto, y identificar con precisión duplicado You-loop. El rendimiento de los productos, multimodal LLM y las variaciones humanas se han desarrollado con avances tecnológicas avanzadas en el mundo real. Desarrollará e implementará soluciones de forma independiente y trabajará con el módulo Cross-Functional Listing Quality, incluidos los productos, diseño, ingeniería, análisis y operaciones, para resolver problemas de extremo a extremo. Lo que hará Impulsará la visión, estrategia y ejecución en ciencia de datos sobre la calidad del listado, utilizando las soluciones ML e IA para mejorar la calidad de las listas de productos de Faires. Utilice aprendizaje profundo, ajuste fino del LLM y capacitación humana en circuito para detectar y abordar automáticamente los problemas con alta precisión. Actúa como líder en el módULO Cross-F functional Listings Quality, pensando de punto a punto sobre experiencias de marca y minorista. La capacidad de diseñar e implementar soluciones ML sin supervisión Las habilidades de comunicación fuertes y la capacidad de trabajar en un equipo altamente transversal Grandes para tener maestría o doctorado en Ciencias Informáticas, Estadísticas o campos STEM relacionados se recomienda mucho Experiencia previa en el listado de calidad del comercio electrónico experiencia previa en la regulación supervisada de sistemas de inferencia LLM multimodales Experiencia anterior en el despliegue y optimización de sistemas LLM a escala (10B+ tokens), con foco en la eficiencia de costes e impacto del producto San Francisco: el rango salarial para este papel es de $192,000 a $264,000 por año. Esta función también será elegible para equidad y beneficios. Todos los miembros de nuestro equipo están participando en el proceso de fundación. Estamos utilizando tecnología y datos para nivelar el campo de juego: estamos aprovechando el poder de la innovación del producto y el aprendizaje automático para conectar marcas y boutiques de todo el mundo, construyendo una comunidad creciente de más de 350.000 propietarios de pequeñas empresas. Construimos productos que nuestros clientes aman: Todo lo que hacemos es finalmente al servicio de ayudar a nuestros clientes a hacer crecer su negocio porque nuestro objetivo es cultivar el pastel no robarle un pedazo de él. Dirigir un pequeño negocio es trabajo duro, pero usar Faire lo hace fácil. Somos curiosos e ingeniosos: Inquisitivos por defecto, exploramos todas las posibilidades, probamos cada suposición y desarrollamos soluciones creativas para los desafíos presentes. Lideramos con curiosidad y datos disponibles en la toma de decisiones, y desde un principio de mentalidad. Trabajaremos con todos los solicitantes para satisfacer sus necesidades individuales de accesibilidad. Para obtener información sobre el tipo de datos personales que Faire recopila de los candidatos, así como las opciones relativas a los datos recogidos acerca de usted, visite la Política de privacidad de Faire. #J-18808-Ljbffr
Develop and deploy scalable deep learning models to improve listing accuracy and quality
Location: San Francisco, California, United States
Compensation: $192,000 - 264,000 USD / year
Job Tags: Operations
About The Role
Senior Data Scientist / Machine Learning Engineer
Faire is an online wholesale marketplace built on the belief that the future is local — independent retailers around the globe are doing more revenue than Walmart and Amazon combined, but individually, they are small compared to these massive entities. At Faire, we’re using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so that small businesses everywhere can compete with these big box and e-commerce giants.
By supporting the growth of independent businesses, Faire is driving positive economic impact in local communities, globally. We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.
About This Role
Faire leverages the power of machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores. At Faire, the Data Science team is responsible for creating and maintaining a diverse range of algorithms and models that power our marketplace. We are dedicated to building machine learning models that help our customers thrive.
As a member of the Brand Data Science team working on Listing Quality, you will be responsible for improving the quality of product listings to help retailers find and evaluate products on Faire. You will use ML and AI to tackle critical challenges, such as enhancing image and text quality, extracting structured product attributes, and accurately identifying duplicates and product variants. You will leverage deep learning, multi-modal LLMs, and human‑in‑the‑loop training to create high‑performance solutions. This space has been evolving rapidly with advancements in AI and you will be at the forefront of applying the latest technology to drive real‑world impact. You will independently design and implement solutions and work with the cross‑functional Listing Quality pod, including product, design, engineering, analytics, and operations, to solve problems end‑to‑end.
What You’ll Do
Drive data science vision, strategy, and execution on Listing Quality, using ML and AI solutions to improve the quality of Faire’s product listings.
Use deep learning, LLM fine tuning, and human‑in‑the‑loop training to automatically detect and address issues with high accuracy.
Act as a lead on the cross‑functional Listing Quality pod, thinking end‑to‑end about brand and retailer experiences.
Qualifications
3+ years of industry experience using machine learning to solve real‑world problems
Experience with relevant business problems (e.g. e‑commerce)
Experience with relevant technical methods (e.g. LLM fine tuning, deep learning, or human‑in‑the‑loop machine learning)
Strong programming skills
An excitement and willingness to learn new tools and techniques
The ability to design and implement ML solutions without supervision
Strong communication skills and the ability to work in a highly cross‑functional team
Great To Haves
Master’s or PhD in Computer Science, Statistics, or related STEM fields is highly recommended
Previous experience in listing quality for e‑commerce
Previous experience in supervised fine tuning of multi‑modal LLMs
Experience deploying and optimizing LLM inference systems at scale (10B+ tokens), with focus on cost efficiency and product impact
Salary Range
San Francisco: the pay range for this role is $192,000 to $264,000 per year.
This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.
Why You’ll Love Working at Faire
We are entrepreneurs: Faire is being built for entrepreneurs, by entrepreneurs. We believe entrepreneurship is a calling and our mission is to empower entrepreneurs to chase their dreams. Every member of our team is taking part in the founding process.
We are using technology and data to level the playing field: We are leveraging the power of product innovation and machine learning to connect brands and boutiques from all over the world, building a growing community of more than 350,000 small business owners.
We build products our customers love: Everything we do is ultimately in the service of helping our customers grow their business because our goal is to grow the pie — not steal a piece from it. Running a small business is hard work, but using Faire makes it easy.
We are curious and resourceful: Inquisitive by default, we explore every possibility, test every assumption, and develop creative solutions to the challenges at hand. We lead with curiosity and data in our decision making, and reason from a first principles mentality.
Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression.
Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs.
For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire’s Privacy Notice.
#J-18808-Ljbffr
In Summary: Senior Data Scientist / Machine Learning Engineer - Listing Quality - Develop and deploy scalable deep learning models to improve listing accuracy and quality . Faire leverages the power of machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores .
En Español: Científico de datos senior / Ingeniero del aprendizaje automático Faire es un mercado mayorista en línea construido sobre la creencia de que el futuro es local minoristas independientes alrededor del mundo están generando más ingresos que Walmart y Amazon combinados, pero individualmente son pequeños en comparación con estas entidades masivas. En Faire, estamos utilizando el poder de la tecnología, los datos y el aprendizaje automatizado para conectar a esta próspera comunidad de emprendedores de todo el mundo. Si cree en la comunidad, únase a nosotros. About This Role Faire aprovecha el poder del aprendizaje automático y las ideas de datos para revolucionar la industria mayorista, permitiendo que los minoristas locales compitan con gigantes como Amazon y grandes tiendas de boxes. En Faire, el equipo Data Science es responsable de crear y mantener una variedad diversa de algoritmos y modelos que impulsan nuestro mercado. Estamos dedicados a construir modelos de aprendizaje automatizado que ayuden a nuestros clientes a prosperar. Como miembro del equipo Brand Data Science que trabaja en Listing Quality, usted será responsable de mejorar la calidad de las listas de productos para ayudar a los minoristes a encontrar y evaluar productos en Faire. Utilizará ML e IA para abordar desafíos críticos de imagen, tales como aumentar rápidamente la calidad y el texto, extraer atributos estructurados de producto, y identificar con precisión duplicado You-loop. El rendimiento de los productos, multimodal LLM y las variaciones humanas se han desarrollado con avances tecnológicas avanzadas en el mundo real. Desarrollará e implementará soluciones de forma independiente y trabajará con el módulo Cross-Functional Listing Quality, incluidos los productos, diseño, ingeniería, análisis y operaciones, para resolver problemas de extremo a extremo. Lo que hará Impulsará la visión, estrategia y ejecución en ciencia de datos sobre la calidad del listado, utilizando las soluciones ML e IA para mejorar la calidad de las listas de productos de Faires. Utilice aprendizaje profundo, ajuste fino del LLM y capacitación humana en circuito para detectar y abordar automáticamente los problemas con alta precisión. Actúa como líder en el módULO Cross-F functional Listings Quality, pensando de punto a punto sobre experiencias de marca y minorista. La capacidad de diseñar e implementar soluciones ML sin supervisión Las habilidades de comunicación fuertes y la capacidad de trabajar en un equipo altamente transversal Grandes para tener maestría o doctorado en Ciencias Informáticas, Estadísticas o campos STEM relacionados se recomienda mucho Experiencia previa en el listado de calidad del comercio electrónico experiencia previa en la regulación supervisada de sistemas de inferencia LLM multimodales Experiencia anterior en el despliegue y optimización de sistemas LLM a escala (10B+ tokens), con foco en la eficiencia de costes e impacto del producto San Francisco: el rango salarial para este papel es de $192,000 a $264,000 por año. Esta función también será elegible para equidad y beneficios. Todos los miembros de nuestro equipo están participando en el proceso de fundación. Estamos utilizando tecnología y datos para nivelar el campo de juego: estamos aprovechando el poder de la innovación del producto y el aprendizaje automático para conectar marcas y boutiques de todo el mundo, construyendo una comunidad creciente de más de 350.000 propietarios de pequeñas empresas. Construimos productos que nuestros clientes aman: Todo lo que hacemos es finalmente al servicio de ayudar a nuestros clientes a hacer crecer su negocio porque nuestro objetivo es cultivar el pastel no robarle un pedazo de él. Dirigir un pequeño negocio es trabajo duro, pero usar Faire lo hace fácil. Somos curiosos e ingeniosos: Inquisitivos por defecto, exploramos todas las posibilidades, probamos cada suposición y desarrollamos soluciones creativas para los desafíos presentes. Lideramos con curiosidad y datos disponibles en la toma de decisiones, y desde un principio de mentalidad. Trabajaremos con todos los solicitantes para satisfacer sus necesidades individuales de accesibilidad. Para obtener información sobre el tipo de datos personales que Faire recopila de los candidatos, así como las opciones relativas a los datos recogidos acerca de usted, visite la Política de privacidad de Faire. #J-18808-Ljbffr