About the Role
The Competitive Defense team is responsible for protecting Uber's data from external sources. We apply techniques to stop critical business data from being harvested by bad actors. We're looking for a motivated independent Senior Software Engineer who can level-up our ability to protect Uber's business data. You'll play a key role in transforming research into robust, deployable solutions that address complex security, identity and privacy challenges across Uber's global infrastructure. A successful applicant will model a bias towards action, entrepreneurial mindset, and adaptability in their day to day work.
---- What the Candidate Will Do ----
You will be
- Responsible for hands-on-implementation of new methodologies, and leveraging existing technologies to build efficient, accurate, and scalable solutions and deploying them into production.
- Lead the strategic planning and execution of defense strategies, providing technical guidance on the latest machine learning technologies and approaches. As a mentor, you foster the development of more junior team members and encourage skill enhancement.
- Take charge in solving complex problems, innovating new solutions to enhance the effectiveness of our abilities. This role involves significant stakeholder communication, requiring the translation of technical details into understandable terms for non-technical stakeholders.
- Manage projects to ensure efficient goal achievement and compliance with legal and internal policies. Your role also includes collaborating with various departments to ensure a unified approach to API security. Overall, you combine expertise in technology with leadership and communication skills, playing a pivotal role in maintaining the organization's digital integrity.
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---- Basic Qualifications ----
- Master's Degree or equivalent in Computer Science, Engineering, Mathematics or related field with 5+yrs of software development experience.
- Proficiency in one of the programming languages (e.g. C, C++, Java, Python, or Go)
- Experience in modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning)
- Proficiency in unsupervised learning techniques, such as clustering, anomaly detection, and neural networks.
- Familiarity with supervised learning, as it often complements unsupervised methods.
- Understanding of feature engineering and dimensionality reduction.
- Famliarity with machine Learning software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib
---- Preferred Qualifications ----
- Cybersecurity Knowledge:
- Understanding of web scraping techniques and countermeasures.
- Awareness of network security, HTTP protocols, and API security.
- Causal ML and Reinforcement Learning
- Ethical Considerations and Compliance:
- Awareness of ethical issues and regulatory compliance related to data privacy and machine learning.
For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.
Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
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.