Senior Machine Learning Engineer

Nubank; São Paulo; Híbrido; BRL 120.000 - 160.000; Tempo integral

Resumo da oferta

A leading financial technology company in São Paulo is hiring a Machine Learning Engineer to connect ML models with infrastructure and deliver value. The role includes deploying models, collaborating with stakeholders, and maintaining ML systems. Ideal candidates will have programming experience and be familiar with cloud services such as AWS or GCP. This position offers a hybrid work model and a comprehensive benefits package, including medical and parental leave.

Serviços

Chance of earning equity

Meal Card

Public Transportation Benefit

Psychological Assistance Program

Medical Plan

Dental Plan

Language Course Program

Learning platform for courses

Extended Parental Leave

Daycare Allowance

Gym Partnerships

30 days of paid vacation

Qualificações

• Experience creating, deploying, and maintaining ML models.
• Familiar with modern development techniques and frameworks.
• Ability to monitor and maintain ML systems.

Responsabilidades

• Interact with stakeholders to apply data science effectively.
• Deploy ML models in batch and real-time scenarios.
• Help build and maintain tooling for scaling operations.

Conhecimentos

Programming experience

Experience with ML models

Familiarity with cloud services

Understanding software engineering principles

Navigating analytical environments

Ferramentas

AWS

GCP

Azure

Descrição da oferta de emprego

About us

Nu was born in 2013 with the mission to fight complexity to empower people in their daily lives by reinventing financial services. We are one of the world’s largest digital banking platforms, serving millions of customers across Brazil, Mexico, and Colombia. For more information, visit our institutional page https://international.nubank.com.br/careers/

ML Engineering at Nubank

Data Science is essential to every part of the business at Nubank, since Day 1. Most areas of the company use data science to some extent. ML Engineers are key to connecting ML models and ML-enabled systems to the rest of our infrastructure, while making sure that they work properly, delivering value to our customers.

As a Machine Learning Engineer, you’re expected to

• Interact with stakeholders from different functions to understand the best way to apply data science and artificial intelligence to our business;
• Monitor and maintain models and ML systems to make sure they are working well as measured by performance, operational and business metrics;
• Deploy ML models both in batch and real-time scenarios, including building pipelines, constructing features and integrating models to other systems;
• Understand the ML model lifecycle, from inception to deployment and steady-state operation;
• Help build and maintain tooling and platforms to scale operations across multiple teams;
• Be familiar with modeling and statistics concepts;

Our ideal candidate

• Has programming experience and is familiar with modern development techniques;
• Has experience creating, deploying and maintaining ML models and ML-enabled systems using modern frameworks;
• Is familiar with cloud-based services from vendors such as AWS, GCP, Azure, etc;
• Is familiar with software engineering and architecture principles and how they enable sustainable and maintainable systems;
• Is familiar with data engineering routines, pipelines and job scheduling frameworks;
• Is able to navigate complex mathematical and analytical environments when needed;

Our Benefits

• Chance of earning equity at Nubank
• Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
• Public Transportation Commuting Benefit (Vale-Transporte)
• NuCare – Psychological, Financial and Legal Assistance Program
• Life Insurance
• Medical Plan
• Dental Plan
• NuLanguage – Language Course Program
• Nucleo - Our learning platform of courses
• Extended Parental Leave
• Daycare Allowance
• Parental Consultancy
• Work-from-home Allowance
• Gym Partnerships
• 30 days of paid vacation

Our Nu Way of Working

Our work model is hybrid and has cycles that can be from two to three months according to the business of expertise. For every eight or twelve weeks of remote work, one will be at the office. Check more information here.