Internship Program: Machine Learning Backend

We’re looking for a Machine Learning Backend Intern for our technical team. This new team member will be instrumental in developing data science solutions from the idea to maturity as we continue to make the retail world a better, more sustainable place.

At Nextail, we empower retailers to create better experiences while using fewer of the world's resources. Nextail’s cloud-based platform uses artificial intelligence, prescriptive analytics, and optimization to deliver agile merchandising decisions. To date, we’re backed by more than $12M in funding from leading venture capital investors and are working with global retailers like Versace, River Island, and Pepe Jeans. 
ML Backend Intern at Nextail:

The goal of the technical and data science teams is to multiply the impact of our product on the business. Data Science Techniques, AI, ML, Optimisation, Simulation, and Visualization, are the tools we always have at hand when we face a problem, but we will never use them in vain. We work together with Product Managers, Developers, Data Scientists, ML Engineers, Data Engineers, and Business Experts to solve the end-to-end problem. Our job is not finished when the model and the end-to-end solution are in production, or after the change management and operational details are closed, not even when we have strong evidence that the solution is solving the user's problem and she is satisfied because after that we continue monitoring our models. The discussion between pairs, working together, and challenging each other, is the fastest way to solve a problem and to grow as a Machine Learning Engineer. We have a culture of sharing, transparency, meritocracy, caring, and trusting each other.

You will: 

• Participate in the development, deployment, and maintenance of the multiple Machine Learning models they are working with.

• Help to instrument the different models that the squad creates, to collect metrics and usage statistics.

• Implement mathematical algorithms or complex computations.

• Influence the whole model production flow and take part in its improvement process.

• Encourage good technical practices in the squad.

• Work closely with the Data Science team, helping in the design of their models to ensure they are scalable.

We offer:

• Paid internship: Your work will be rewarded and comes with the opportunity to convert into a permanent job.

• Mentoring Program: We will invest in you to gain knowledge and mentor you to develop a career path.

• High flexibility: We’re strong believers that what matters most are results. Each Nextailer is empowered, through trust and ownership, to organize their time as they see fit without jeopardizing the time or work of their colleagues.

• Remote-first philosophy: Nextail started as a remote company and continues to offer a nice mix of remote and/or office-based environments around the world.

• International environment: We operate across the globe, with recent operations reaching from Europe all the way to Australia, and our team alone consists of professionals of more than 15 different nationalities. While many of us are multilingual, our working language is English.

• Diversity on all levels: United as a single team, we celebrate diversity in every dimension*. Professionally speaking, are you ready to work alongside tech geniuses, data science magicians, and fashionistas? You’ll have teammates with extensive experience in a wide variety of professional fields, including technology, retail, consulting, and entrepreneurship.

Requirements

• You must have the ability to work through an internship agreement (“Convenio”)

• You are fluent in English (other languages, especially Spanish, are a plus) and are interested in working in an international company.

• Curiosity and passion for new technologies.

• Comfortable working in high-performance computational environments (Apache Spark, Databricks).

• Theoretical and practical experience building pipelines for Data Science teams.

• Business-oriented. You acknowledge software is not the end but a means to get business value (but this doesn’t mean doing crappy code). You are willing to learn