Middle/Senior Machine Learning Engineer
Location:
Other, LATAM
Seniority:
Senior
Technologies:
Python

At the project, we’re applying the latest advances in AI to fashion retail. We’re using NLP,

computer vision, and deep representation learning to, among other things:

  • Parse the textual and visual data for our millions of products

  • Serve up personalized and delightful recommendations suited to each of our customer’s

unique tastes

  • Power an interface that can process customer queries through conversation and provide

product and styling recommendations

We’re looking for passionate and skilled machine learning engineers who are excited by the

work of architecting, training, evaluating, and deploying machine learning systems to be able to

solve these problems

  • You’ll work with cross-functional teams of engineers, data scientists, product managers,

and subject matter experts to build machine learning applications in fashion retail and

drive business value

  • Your focus will be on the AI at the heart of these applications: the design, training,

evaluation, and deployment of the models

  • You’ll bring your broad expertise in AI, weighing the wide range of possible models and

approaches, helping the team make informed and strategic decisions

  • Excellent communication and collaboration skills

  • 2+ years of hands-on (non-internship) experience with machine learning and software

development in industry. Solid grasp of the fundamentals of and, crucially, the practice of

machine learning.

  • Deep understanding of and experience with large language models: design patterns,

agentic workflows, training/fine-tuning strategies, data gathering/curation, prompting,

evaluation

  • Strong expertise in Python and PyTorch. Proficiency with other relevant machine

learning libraries and frameworks.

  • Experience with cloud platforms and commonly used services for model training and

deployment

Nice to have:

Bachelor’s degree with coursework in computer science, statistics, mathematics, or

related fields

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