Sr. Staff Machine Learning Engineer

This critical role is responsible for leading the technical vision and hands-on implementation of an adversarial machine learning problem. Due to the evolving and dynamic nature of the problem space, you’ll need to keep up-to-date with the state of the art techniques and, as a mentor, foster the development of the team to enhance their skill set.

This role involves significant stakeholder communication to the highest levels of leadership, requiring the translation of technical details into understandable terms for all involved. You’ll be guiding the day-to-day activities of the team as well as the longer term charter.

This role is high-impact, fast-moving and requires an individual who can be successful in a highly adaptable environment. It's an adversarial problem that will keep you interested, challenging your skills to be able to detect bad actors as they evolve and to do it in near real-time at high-scale.

What the Candidate Will Do:

• Lead small engineering group to protect Uber's marketplace data
• Set technical vision and socialize it across the company
• React quickly to the ever changing threat landscape

Basic Qualifications:

• Knowledge of different compilation steps (and ability to fix) in languages such as Go, C, C++, or Java.
• Excellent communication skills and the ability to collaborate effectively with cross-functional teams
• Ability to mentor and grow a group of other Software Engineers
• Ability to lead projects with several cross-org dependencies and design complexities
• Large-scale training using data structures and algorithms
• Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning)

Preferred Qualifications:

• PhD or equivalent in Computer Science, Engineering, Mathematics or related field
• 8+ years of experience in professional software development experience, developing and deploying systems in production environments
• Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib
• Excellent communication skills and the ability to collaborate effectively with cross-functional teams
• Ability to mentor and grow a group of other Software Engineers
• Anomaly Detection Techniques
• Deep Learning
• Scalable ML architecture
• Feature management
• Causal ML
• Reinforcement learning

For New York, NY-based roles: The base salary range for this role is USD$252,000 per year - USD$280,000 per year.

For San Francisco, CA-based roles: The base salary range for this role is USD$252,000 per year - USD$280,000 per year.

For Seattle, WA-based roles: The base salary range for this role is USD$252,000 per year - USD$280,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$252,000 per year - USD$280,000 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 .

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 .

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.