Lead Machine Learning Engineer

Shotgun is a leading platform dedicated to empowering live music event organizers and touring artists, driving the future of the live music industry. Our mission is to build the infrastructure that enables live music to thrive. We provide powerful tools to sell tickets, build strong brands, and connect with fans in meaningful ways.From 2020 to 2024, Shotgun achieved rapid growth with GMV increasing 20x and revenue growing 30x - leading the company to profitability. Today, we support over 6,000 clients and engage more than 6,000,000 users across Europe, the US, and LATAM.Our exponential growth rests on two core pillars:

The Best Product in the Industry
We shipped many game-changing B2C and B2B features in the past 3 years, continually innovating to help change the live music ecosystem.

A Committed Go-to-Market Team

Our team of industry experts is deeply passionate and relentlessly focused on delivering value to our clients, partners and users alike.

In the past seven years, Shotgun has raised €10M from Newfund, Venrex, One RagTime, Creator Collective, and BPI Culture Fund. We are a lean and dynamic team of 80 people, with offices in Paris, Miami, São Paulo, Lisbon, and Marseille.Our culture is built on passion, commitment, ownership, and humility. For French speakers, you can learn more about our journey by listening to We Are Sales, a podcast featuring our CEO, Tristan

We're looking for individuals who want more than just a job. People willing to get out of their comfort zone to reach outstanding goals. Doers who never stop learning. We want people who are talented, optimistic and fun: who set the bar high but don't take themselves too seriously. 

Shotgun historically has been growing as an electronic music live event platform. It has been growing that way organically from word of mouth and sales effort. As we are expanding in new geographies and new music verticals, our objective is to refine how events and users are matched to enhance relevance and the user experience. This encompasses not only user preferences but also equipping organizers with insights to book artists aligned with audience tastes and explore deeper into their preferences.

To achieve this, we're looking for a talented individual to join our team and establish a machine learning-based content management and recommender system.

• Work closely with the Strategy and Product teams to proactively explore opportunities for leveraging data science and machine learning, driving innovation, maintaining a competitive edge, and delivering exceptional value to users, partners, and customers.
•  Lead the research and development of cutting-edge recommender systems, among other applied data science and machine learning projects, with a focus on balancing experimentation, learning, and return on investment.
• Partner with Product teams to translate research into production-ready features, making informed simplifications and adapting systems to production constraints as needed.
• Battle test your reasearch and models by running extensive data analysis, turning complex models into easy to grasp visual representations of what your models effectively learned.
• Advocate for and promote scientific research methodologies and the use of machine learning within the company, effectively engaging both internal and external stakeholders.
• Establish strong foundations for a research team by streamlining and industrializing machine learning and data science project development, enhancing the company's Machine Learning Platform and associated processes.

• You have a sharp analytical mindset and a solid academic background preferably a PHD in Mathematics,Computer Science or Machine Learning or Master degree in Engineering.
• You have a gift for abstraction and identifying complex mathematical concepts can be tweaked to solve real world problems.
• You have at least 5 years of hands-on experience in machine learning related roles with a previous experience with recommandation systems and non-textual data embeddings.
• You prioritize user-centric, practical solutions over costlier cutting-edge alternatives
  
• You are a critical thinker. No matter the given performances of your models you will challenge them in every possible way paying extra attention to what your model actually learn keeping in mind socio-demographical biaises that could lead to involuntary discriminations. 
• You have solid Data Analytics and Machine Learning skills - Experience developing with machine learning framework in production is a requirement.
• You having an advanced understanding of Software Engineering and are good at transitioning Machine Learning proof of concepts into robust systems building around production environment constraints.
• You are actively seeking feedback and input from teammates to uncover opportunities, define project scopes, and address challenges.
• You are fluent in English and French, and are able to communicate with the team across multiple offices.
• You are passionate about entertainment: it doesn't matter which industry, but entertaining people makes you happy: music, gaming, events,...
• Note to women : Shotgun as a company value gender and origin diversity not because it sells to applicants but most importantly because it is necessary to scale in a healthy manner and boost creativity. Problem is women tend to apply less often when they think they don't match all job requirements. So if you think you're not matching 100% of the requirements, no matter your gender, please apply

Team Off-sites and team moments: We organise a lot of team moments at Shotgun, because the team is precious to us

Shotgun events vouchers : you will get shotgun credits every quarter

Gymlib : Shotgun promotes sport activity; you will get preferential rates for various sports halls

Sustainability mobility bonus: in order to encourage the use of sustainable transportation means, you will be granted a contribution if you are using a personal bike, for example, to get to work.

Swile Lunch Card: Lunch card and much more:

Alan Health Insurance: We got you covered with Alan

Childcare

We like to move fast but want to give you a chance to meet as much team members as possible:

• Introductory meeting with our Head of data (1 hour)
• Take Home Case Study (4-6 hours)
• Case Study debriefe with our Head of data (30 min)
• Interview with our CFO and CPO (1 hour)