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Staff Machine Learning Engineer, Delivery Matching

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Uber

Jul 5, 2024

Applications are closed

  • Job
    Full-time
    Senior Level
  • Software Engineering
  • $218K - $242K
  • New York, +1

Requirements

  • PhD or equivalent experience in Computer Science, Engineering, Mathematics or a related field and 6 years of Software Engineering work experience.
  • Experience in programming with a language such as Python, C, C++, Java, or Go.
  • Experience with ML packages such as Tensorflow, PyTorch, JAX, and Scikit-Learn.
  • Experience with SQL and database systems such as Hive, Kafka, and Cassandra.
  • Experience in the development, training, productionization and monitoring of ML solutions at scale.
  • Preferred Qualifications
  • Experience in a technical leadership role and mentoring junior engineers.
  • Experience in modern deep learning architectures and probabilistic models.
  • Experience in optimization (RL / Bayes / Bandits) and online learning.
  • Experience in causal inference/personalization/ranking

Responsibilities

  • Lead the design, development, optimization, and productization of machine learning (ML) solutions and systems that are used to solve strategically important or vaguely defined problems.
  • Build ML solutions to improve Delivery marketplace efficiency while delivering magical user experience
  • Lead ML engineers, provide technical leadership and vision for the team.

FAQs

What is the primary responsibility of a Staff Machine Learning Engineer, Delivery Matching?

The primary responsibility of a Staff Machine Learning Engineer, Delivery Matching is to lead the design, development, optimization, and productization of machine learning solutions and systems used to solve strategically important problems in the Delivery marketplace.

What qualifications are required for a Staff Machine Learning Engineer, Delivery Matching?

The basic qualifications for this position include a PhD or equivalent experience in Computer Science, Engineering, Mathematics, or a related field, 6 years of Software Engineering work experience, programming experience in languages such as Python, C, C++, Java, or Go, experience with ML packages like Tensorflow, PyTorch, JAX, and Scikit-Learn, proficiency in SQL and database systems like Hive, Kafka, and Cassandra, as well as experience in developing, training, productizing, and monitoring ML solutions at scale.

What are some preferred qualifications for a Staff Machine Learning Engineer, Delivery Matching?

Some preferred qualifications for this position include experience in a technical leadership role and mentoring junior engineers, expertise in modern deep learning architectures and probabilistic models, knowledge of optimization techniques like RL/Bayes/Bandits and online learning, as well as experience in causal inference, personalization, and ranking algorithms.

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Uber

We reimagine the way the world moves for the better.

Technology
Industry
10,001+
Employees
2009
Founded Year

Mission & Purpose

We are Uber. The go-getters. The kind of people who are relentless about our mission to help people go anywhere and get anything and earn their way. Movement is what we power. It’s our lifeblood. It runs through our veins. It’s what gets us out of bed each morning. It pushes us to constantly reimagine how we can move better. For you. For all the places you want to go. For all the things you want to get. For all the ways you want to earn. Across the entire world. In real time. At the incredible speed of now. The idea for Uber was born on a snowy night in Paris in 2008, and ever since then our DNA of reimagination and reinvention carries on. We’ve grown into a global platform powering flexible earnings and the movement of people and things in ever expanding ways. We’ve gone from connecting rides on 4 wheels to 2 wheels to 18-wheel freight deliveries. From takeout meals to daily essentials to prescription drugs to just about anything you need at any time and earning your way. From drivers with background checks to real-time verification, safety is a top priority every single day. At Uber, the pursuit of reimagination is never finished, never stops, and is always just beginning.

Culture & Values

  • Go get it

    Bring the mindset of a champion. Our ambition is what drives us to achieve our mission. How we define a champion mindset isn’t based on how we perform on our best days, it’s how we respond on the worst days. We hustle, embrace the grind, overcome adversity, and play to win for the people we serve. Because it matters.

  • Trip obsessed

    Make magic in the marketplace. The trip is where the marketplace comes to life. The earner, rider, eater, carrier and merchant are the people who connect in our marketplace - and we see every side. This requires judgment to make difficult trade-offs, blending algorithms with human ingenuity, and the ability to create simplicity from complexity. When we get the balance right for everyone, Uber magic happens.

  • Build with heart

    We care. We work at Uber because our products profoundly affect lives and we care deeply about our impact. Putting ourselves in the shoes of the people who connect in our marketplace helps us build better products that positively impact our communities and partners. Our care drives us to perfect our craft.

  • Stand for safety

    Safety never stops. We embed safety into everything we do. Our relentless pursuit to make Uber safer for everyone using our platform will continue to make us an industry leader for safety. We know the work of safety never stops, yet we can and will challenge ourselves to always be better for the communities we serve.

  • See the forest and the trees

    Know the details that matter. Building for the intersection of the physical and digital worlds at global scale requires seeing the big picture and the details. Knowing the important details can change the approach, and small improvements can compound into enormous impact over time.

  • One Uber

    Bet on something bigger. It’s powerful to be a part of something bigger than any one of us, or any one team. That’s why we work together to do what’s best for Uber, not the individual or team. We actively support our teammates, and they support us - especially when we hit the inevitable bumps in the road. We say what we mean, disagree and commit, and celebrate our progress, together.

  • Great minds don't think alike

    Diversity makes us stronger. We seek out diversity. Diversity of ideas. Identity. Ethnicity. Experience. Education. The more diverse we become, the more we can adapt and ultimately achieve our mission. When we reflect the incredible diversity of the people who connect on our platform, we make better decisions that benefit the world.

Benefits

  • Comprehensive Healthcare

  • Flexible Work

  • Uniquely Uber

  • Health & Wellness