Uber| Palo Alto | Fulltime | Backend| FE/Full Stack | ML Engineer
Uber, Advanced Technologies, Engineering is the Palo Alto, CA division of the Uber Engineering Team: a high-performance culture marked by fearlessness and achievement. We focus on the development of key technologies that advance Uber’s mission of bringing safe, reliable transportation to everyone, everywhere. Our work is primarily in the areas of mapping and sensing.
1. Backend - https://www.uber.com/careers/list/12746/ 2. FE/Full Stack - https://www.uber.com/careers/list/20130/ 3. ML Engineer - https://www.uber.com/careers/list/15108/
Note : Prior Mapping experience is not mandatory. The work you will do will be hugely impactful. The experience you will gain will be unique and unmatched.
Apply or get in touch at heenat at uber.com
zlatan_is_red 30 days ago [-]
Uber is a really nice place to build a product with a great sense of ownership. You'll be working with a highly motivated peer group, on some of the hardest problems in the real world. As an engineer, it's a very rewarding experience in scaling your implementation to serve the magical trip to millions of users every day.
Disclaimer: I work in the team.
Uber's Amsterdam engineering office is looking for back-end, Android and iOS engineers for its teams:
* Payments: do you want to build the future of payments for on-demand services?
* Mobile platform: are you passionate about tooling that makes developer more productive?
Uber, Advanced Technologies, Engineering - Imagery is the Palo Alto, CA division of the Uber Engineering
Team: a high-performance culture marked by fearlessness and achievement. We focus on the development of key technologies that advance Uber’s mission of bringing safe, reliable transportation to everyone, everywhere. Our work is primarily in the areas of mapping and sensing.
Note : Prior Mapping experience is not mandatory. The work you will do will be hugely impactful. The experience you will gain will be unique and unmatched.
Uber is a really nice place to build a product with a great sense of ownership. You'll be working with a highly motivated peer group, on some of the hardest problems in the real world. As an engineer, it's a very rewarding experience in scaling your implementation to serve the magical trip to millions of users every day.
We’re presently seeking people with these qualities to join Uber's Map Automation subteam, a team that uses our extensive imagery and trace data for mapping applications to build data pipelines that extract valuable bits of information from imagery and GPS data in order to optimize and augment maps. This will have a direct impact on both riders and drivers by helping them connect faster and more efficiently. We are looking for a seasoned software engineer who has a solid grasp of machine learning theory and statistical inference - someone who is able to whiteboard some theory while at the same time is able to roll up his/her sleeves and get coding. We expect the person to be able to read and understand research papers and be able to translate the ideas into efficient code. We also expect the person to be data oriented - i.e. be able to set up experiments to measure things that will in turn drive decisions.
Successful candidates should have:
Strong programming skills in either Java, C++, or Python
Experience with developing big-data processing pipelines over Hadoop or similar technologies.
Experience with developing systems for detection, recognition, classification, entity-matching, etc.
Experience with machine learning/statistical inferencing technologies such as random forests, deep nets., Bayesian nets, etc.
Experience in mapping, or computational geometry is a plus.
A Ph.D. in a quantitative field preferred but not required.
zlatan_is_red 30 days ago [-]
Uber is a really nice place to build a product with a great sense of ownership. You'll be working with a highly motivated peer group, on some of the hardest problems in the real world. As an engineer, it's a very rewarding experience in scaling your implementation to serve the magical trip to millions of users every day. Disclaimer: I work in the team.