Software Engineer II - Engineer

Uber; Sunnyvale (CA); On-site; USD 171,000 - 190,000; Full time

Benefits offered by this job

Bonus program

Equity award

401(k) plan

Benefits

Job summary

Uber Technologies Inc. is seeking a Machine Learning Engineer for the UberEats Feed Ranking team in Sunnyvale, CA. You will own and develop models across the entire ranking stack, from retrieval to post-ranking, handling large-scale, low-latency serving requirements.

The role requires strong Python/Go/Java skills, experience with PyTorch/TensorFlow, and expertise in distributed data processing. You will work with backend engineers and product partners to maximize business impact while advancing

Qualifications

• Bachelor’s degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 3+ years of full-time experience on production ML systems.
• Strong proficiency in Python, Go, or Java.
• Strong proficiency with deep-learning frameworks (PyTorch, TensorFlow/Keras, JAX).
• Experience with distributed data processing and ETL frameworks (Spark, Ray Data).
• Strong technical communication and ability to manage multiple cross-functional stakeholders.

Responsibilities

• Own and develop on all parts of the ML lifecycle - offline training and online serving efficiency.
• Leverage SOTA ML techniques from DLRM and LLM literature into the modeling stack.
• Collaborate with backend engineers to ensure high-quality end-to-end integration.
• Coordinate with Science and Product partners to maximize business impact of ML improvements.

Skills

Python/Go/Java

DL frameworks (PyTorch, TensorFlow, K"

Education

Bachelor's degree or equivalent in CS/Engineering/Math

Master's or PhD in CS/Engineering/Math (preferred)

Tools

Spark

Ray Data

PyTorch

TensorFlow/Keras

JAX

Job description

About the Role

The UberEats Feed Ranking team is responsible for the ML ranking layer which personalizes the Eats Homefeed. This personalization layer is one of the main drivers of order growth across the Delivery organization. As a Machine Learning Engineer (MLE) on the Feed Ranking team, you will own and develop models across our entire ranking stack (Retrieval + Pre-Ranking, Second Pass Ranking, Post-Ranking). Our models are sophisticated (>5B parameters), our features are rich (near-realtime engagement history with 1-year lookback), and our serving requirements are stringent (>10M QPS with low latency and high availability). As an MLE, the reward for working within these requirements is significant - offline performance gains in our ranking models are strongly correlated with topline impact for the entire Eats business.

What You’ll Do

• Own and develop on all parts of the ML lifecycle - both offline (training, model architecture, etc.) and online (serving efficiency, GPU provisioning + utilization, etc.).
• Bring SOTA ML techniques from DLRM and LLM literature (Scaling Laws, Kernel Fusion, Latent Attention, Agentic Auto-Research, RL-based post-ranking, etc.) into our modeling stack.
• Collaborate closely with backend engineers to ensure high-quality and reliability in end-to-end integration.
• Coordinate with Science and Product partners to maximize the business impact of ML improvements.

Basic Qualifications

• Bachelor’s degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 3+ years of full-time experience working on production ML systems.
• Strong proficiency in at least one programming language such as Python, Go, or Java.
• Strong proficiency with common Deep-Learning frameworks (PyTorch, Tensorflow/Keras, Jax, etc.).
• Experience with distributed data processing and ETL frameworks (Spark, Ray Data, etc.).
• Strong technical communication and ability to manage multiple cross functional stakeholders.

Preferred Qualifications

• Master's or PhD in Computer Science, Engineering, Mathematics or related field, with publications in the ML/AI space (papers, conference presentations, company technical blogs, etc.).
• Industry experience working on Deep Learning Recommendation Systems and/or LLM model development at scale in a production/user-facing environment.
• Experience optimizing Deep Learning model architectures + serving stack to improve GPU MFU across different hardware types.
• Desire to grow into technical leadership and become a force multiplier for junior engineers.

For San Francisco, CA-based roles: The base salary range for this role is USD $171,000 per year - USD $190,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD $171,000 per year - USD $190,000 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. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.

Ready to Ride?

This isn't the kind of place where you follow a playbook — it's where you help write one.

You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits.

Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.

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.