About the Role Contributes to the design, development, optimization, and productionization of machine learning (ML) or ML-based solutions and systems that are used within a team to solve well-defined problems leveraging the support and guidance of others on the team. This role also learns to use and improve ML infrastructure for model development, training, deployment needs and scaling ML systems.

About the Team

ML Foundations in Uber Eats is deeply engaged in foundational work that impacts many products within Uber Eats. Our team develops key modeling artifacts critical for our business, including entity classifications, entity resolution, attribute enrichments, semantic similarity and complementary recommendation models, and user profiles. We adopt cutting-edge, robust machine learning building blocks for Uber Eats .

We are on the lookout for individuals who demonstrate exceptional problem-solving skills, critical thinking, and a strong foundation in coding. Ideal This role offers the opportunity to work across all levels of the ML stack, spanning from infrastructure to ML model development and productionisation.

What the Candidate Will Do

- Develop and productionize machine learning algorithms for multiple business problems
- Deeply engage with product datasets analyze them to understand and drive product insights, further model iterations.
- Continuously innovate and apply state-of-the-art ML algorithms at Uber Scale.
- Establish best practices and improve the rigor and bar of ML in Uber Eats

Minimum Qualifications

Completing a Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics, or a related field, plus a 3-months total software engineering experience gained through work, education, coursework, training, research or similar in any area.

- Proficiency in one or more object-oriented programming languages such as Python, Go, Java, C++.
- Experience with big-data architecture, ETL frameworks, and platforms (e.g., Hive, Spark, Presto)
- Working knowledge of contemporary machine learning and deep learning frameworks (e.g. PyTorch, TensorFlow, JAX).

Preferred Qualifications

- Multimodal Classification (Natural Language Processing, Computer Vision)
- Experience building reusable embeddings, applications and fine tuning of large language models.
- Deep understanding of all aspects of machine learning model lifecycles (from prototypes, feature engineering, training, inference, deployment, monitoring).
- Strong statistical and experimental foundation and acumen to develop insights from data.

At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 600 cities around the world!

We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have a curiosity, passion and collaborative spirit, work with us, and let's move the world forward, together!

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](https://forms.gle/aDWTk9k6xtMU25Y5A).

For San Francisco, CA-based roles: The base salary range for this role is USD$140,000 per year - USD$147,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$140,000 per year - USD$147,000 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](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](https://forms.gle/aDWTk9k6xtMU25Y5A).

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.