Sr Machine Learning Engineer

Uber; São Paulo; Híbrido; BRL 80.000 - 150.000; Tempo integral

Resumo da oferta

An innovative firm is seeking a seasoned software engineer to join their Rider ML team, dedicated to enhancing rider engagement through advanced machine learning solutions. In this role, you will develop and deploy state-of-the-art deep learning models that operate in real-time, optimizing personalized recommendations and driving high revenue. This position offers the opportunity to work on impactful projects that influence millions of users while collaborating with a diverse team of experts. If you are passionate about machine learning and eager to make a difference, this role is perfect for you.

Qualificações

• 5+ years of software engineering experience with a focus on ML.
• Strong problem-solving skills and expertise in ML methodologies.

Responsabilidades

• Develop advanced intent modeling and ranking solutions.
• Build and deploy ML models at scale for high reliability.

Conhecimentos

Machine Learning

Deep Learning

Problem-Solving

Data-Driven Methodologies

Statistical Methods

Formação académica

Bachelor’s degree in Computer Science

PhD in Computer Science

Ferramentas

TensorFlow

PyTorch

JAX

Python

Spark SQL

Presto

Go

Java

Descrição da oferta de emprego

Please note: this hybrid position is based in São Paulo, Brazil - welcoming both local professionals and those open to relocating to São Paulo.

About the Team

The Rider ML team is dedicated to developing machine learning infrastructure and ranking solutions that enhance rider engagement across various touchpoints within our platform. This includes optimizing the rider homepage ranking (Project Lumos) and product selection ranking (Project Aura), among other key engagement screens. Each month, millions of users interact with our platform to request on-demand rides, explore vertical offerings like reservations and rentals, take advantage of relevant promotions, order food and groceries, and subscribe to membership services. Our goal is to recommend the most relevant products based on each user's session intent.

Our mission is to build advanced ML infrastructure and algorithms that enable real-time, dynamic personalization of rider surfaces, ensuring a tailored experience for every session. Beyond the homepage and product selection screens, our personalization efforts span multiple engagement touchpoints, including activity feeds, service pages, trip experiences, and other critical moments throughout the rider journey.

About the role

We are dedicated to enhancing the rider experience through cutting-edge machine learning, delivering personalized recommendations and tailored services at scale. Our team develops and deploys state-of-the-art deep learning models that operate in real-time with ultra-low latency, powering experiences that drive high revenue.

What You’ll Work On:

• Developing advanced intent modeling and ranking solutions to optimize personalized recommendations.
• Striking the right balance between ranking relevance and discovery (exploration vs. exploitation).
• Researching and integrating new signals to improve key ranking metrics and user engagement.
• Building and deploying ML models at scale, ensuring high reliability and quality in online serving.

Basic Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics or related field
• 5+ years of experience in software engineering with an emphasis on data-driven methodologies, deep learning, and online experimentation
• Strong problem-solving skills, with expertise in ML methodologies
• Experience in applying ML, statistics, or optimization techniques to solve large-scale real-world problems (e.g. ads tech, recommender systems)
• Industry experience in ML frameworks (e.g. Tensorflow, Pytorch, or JAX) and complex data pipelines; programming languages such as Python, Spark SQL, Presto, Go, Java

Preferred Qualifications

• 5+ years of experience in software engineering specializing in applied ML methods
• Experience in designing and crafting scalable, reliable, maintainable and reusable ML solutions using deep-learning techniques and statistical methods.
• Innate truth-seeker who values and produces analytic evidence and insight, as well as translating them and business goals into technical problems and solutions.
• 1+ years of experience working in a cross-functional and/or cross-business projects, partnering with Product, Scientists, and cross-org leads to shape the team’s strategies
• Passionate about helping junior members grow by inspiring and mentoring engineers
• Resilience, determination, ownership mindset
• PhD degree in Computer Science, Engineering, Mathematics or related field

We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world forward, together.

Offices continue to be central to collaboration and Uber’s cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

*Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to [e-mail].