Sr Software Engineer, ML

Join Uber's Engineering Security organization as part of our growing AI/ML initiatives. Our mission is to advance security and privacy through AI, focusing on building intelligent systems that strengthen protection, enable the safe adoption of AI technologies, and address emerging risks in AI-enabled environments.

About the Role

As a Senior Machine Learning Engineer, you will build and scale machine learning and GenAI-powered systems that operate in production. You will work closely with applied scientists and engineers to develop, deploy, and improve models and services that help address real-world security and privacy challenges.

This role is ideal for engineers who enjoy working across the ML lifecycle, from data and training pipelines to model deployment, evaluation, and production monitoring, and who are excited about applying modern machine learning techniques including large language models to practical problems.

Basic Qualifications

1\\. 6+ years of industry experience - Build and maintain production-grade ML and GenAI systems2\\. Design and implement training, fine-tuning, and feature engineering pipelines

3\\. Develop scalable workflows for experimentation, model iteration, and evaluation

4\\. Partner with applied scientists to productionize models and improve performance

5\\. Integrate ML and LLM capabilities into backend services and real-world workflows

6\\. Build systems for evaluation, benchmarking, monitoring, and continuous improvement

7\\. Optimize inference workflows for latency, reliability, and scalability

8\\. Contribute to systems that detect and mitigate risks in AI-enabled environments

Preferred Qualifications

1\\. Experience building or deploying LLM-based or GenAI-powered applications in production

2\\. Experience with prompt engineering, model evaluation, or retrieval-augmented generation techniques

3\\. Experience building end-to-end ML systems from data preparation through deployment and monitoring

4\\. Experience optimizing model inference for low-latency or real-time use cases

5\\. Understanding of model quality evaluation, experimentation, and iteration workflows

6\\. Exposure to security, privacy, trust, safety, or risk-related domains

7\\. Familiarity with adversarial machine learning, AI safety, or abuse detection concepts

Why Join Us

1\\. Work on impactful ML and GenAI systems in a high-scale, real-world environment

2\\. Collaborate with a multidisciplinary team of engineers and scientists

3\\. Build and deploy systems that directly influence safety, security, and reliability

4\\. Help shape how modern AI technologies are applied responsibly in critical domains

For Sunnyvale, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year.

You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link [](;br>
Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity 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](;br>
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.