On the Rides Engineering team, we write code that ignites opportunities for millions of people every day. We're focused on making Uber's cor...
On the Rides Engineering team, we write code that ignites opportunities for millions of people every day. We're focused on making Uber's core ridesharing products faster, safer, and more reliable by building scalable software solutions for riders and drivers on our platform.
About the Role
We have established a world-class Rider Intelligence engineering team to build critical machine learning solutions and frameworks to empower Uber's core Rider products. Our team's mission is to serve the ML needs of the entire Uber Rider organizations (> 200 people). In this role, you can have a significant impact on a wide range of Uber rider products and Uber consumers. We work on everything from enhancing rider growth and deepening engagement to growing Uber's footprint in the multi-modal trip marketplace. You will be on a super collaborative team designed to maximize your ability to deliver results. If you are motivated by building technically challenging machine learning and optimization problems in real-time and at scale, working on projects that impact every single Uber rider, knowing that every Uber rider sees and benefits from your work, and helping to drive Uber's top business metrics, then Rider Intelligence is the team for you at Uber!
What You'll Do
- Build ML solutions to solve business needs across the Rider organization with over 200 engineers. Some of the types of projects you will work on:
- Build a personalized real-time ride product recommendations engine to suggest the right products to the riders at the right time, to shift behavior, and improve the rider experience.
- Supercharge Uber's rides and eats subscription upsells, target benefits incentives based on user interest and product usage, and impact Uber's business goals by improving acquisition and engagement.
- Build shareable ML tools and frameworks to serve the ML needs of the entire Rider org
- Ranking engine infrastructure to onboard personalized rider level recommendation ML use cases such as message targeting or benefits targeting, just to name a few!
- 7+ years of industry experience with a master or bachelor degree.*
- 2+ years of experience building and productionizing innovative end-to-end Machine Learning systems.
- Proven engineering and coding skills. Ability to write high-performance production quality code. Experience in Java, Go, Python and other equivalent languages is a plus.
- Strong understanding of common families of models, feature engineering, feature selection, optimization algorithms
- Proven track record to choose the right ML solutions to solve the problem within current constraints while having a clear vision of the next iterations and a good balance between exploration and exploitation of different techniques.
- Experience with MapReduce, Spark and Hive on large datasets.
*Role initiatlly posted with incorrect required years of experience:Basic Qualifications changed from 5+ years of required experience to 7+ yearsPreferred Qualification changed from 3+ years of experience to 5+ years
- 5+ years of experience with a PhD in relevant fields (CS, EE, Math, Stats, Physics, etc.)*
- Proven experience developing complex software systems scaling to millions of users with production quality deployment, monitoring and reliability.
- Passion to use machine learning to empower Uber products.
- Ability to go deep and build the most impactful solutions while also leading multiple directions across multiple teams and organizations to ensure the success of our mission.
- Proven experience in simplifying/converting business problems into ML problems.
- provided by Dice