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Machine Learning Engineer

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Uber

3mo ago

  • Job
    Full-time
    Junior & Mid Level
  • Data
  • Sunnyvale, +2

AI generated summary

  • You need a Bachelor's degree in Computer Science or related field, 2+ years of engineering experience, multiple multi-functional team experience, expertise in Python/Go/Java/C++, ML/economics experience, and knowledge of ML technologies & big-data architecture.
  • You will design, build, and deploy ML models, review teammates' work, collaborate with cross-functional teams for new solutions daily at Uber.

Requirements

  • Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 2+ years of full-time engineering experience or PhD new grad
  • Experience working with multiple multi-functional teams(product, science, product ops etc).
  • Expertise in one or more object-oriented programming languages (e.g. Python, Go, Java, C++).
  • Preferred Qualifications:
  • 1+ year of ML/economics experience and building ML/economic models
  • Experience with the design and architecture of ML systems and workflows.
  • Experience with building algorithmic solutions in production, making practical tradeoffs among algorithm sophistication, compute complexity, maintainability, and extensibility in production environments.
  • Experience with taking on vague business problems, translating them into ML + Optimization formulation, identifying the right features, model structure and optimization constraints, and delivering business impact.
  • Experience with optimizing Spark queries for better CPU and memory efficiency.
  • Working knowledge of latest ML technologies, and libraries, such as PyTorch, TensorFlow, JAX, Ray, etc.
  • Experience owning and delivering a technically challenging, multi-quarter project end to end.
  • Experience with big-data architecture, ETL frameworks and platforms, such as HDFS, Hive, MapReduce, Spark, , etc.

Responsibilities

  • Design and build Machine Learning models with optimization engines.
  • Productionize and deploy these models for real-world application.
  • Review code and designs of teammates, providing constructive feedback.
  • Collaborate with Product and cross-functional teams to brainstorm new solutions and iterate on the product.

FAQs

What qualifications are required for the Machine Learning Engineer role at Uber?

Candidates should have a Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics, or a related field, with 2+ years of full-time engineering experience or a PhD new grad. They should also have experience working with multiple multi-functional teams, expertise in object-oriented programming languages, and ideally 1+ year of ML/economics experience.

What responsibilities will the Machine Learning Engineer have at Uber?

The Machine Learning Engineer will design and build ML models with optimization engines, productionize and deploy these models for real-world application, review code and designs of teammates, and collaborate with Product and cross-functional teams to brainstorm new solutions and iterate on the product.

What is the salary range for Machine Learning Engineers at Uber in different locations?

For San Francisco, CA-based roles, Seattle, WA-based roles, and Sunnyvale, CA-based roles, the base salary range for Machine Learning Engineers is USD$158,000 per year - USD$175,500 per year.

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