2,078,996open jobs
127,431companies
241,615added this week
Browse all
Salary
$267k – $297k per year
Location
In office (San Francisco, New York, Seattle)
Seniority
Staff · 12+ years exp
Visa
H-1B filings in 12 months: 837 · for this role: 529 · green card filings: 258

Confirmed on the employer's own hiring board on Nov 3, 2026. First seen by Alion on Oct 23, 2026. Uber scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Uber is an American mobility and delivery company founded in San Francisco in 2009 that connects independent drivers and couriers with riders and customers through its apps. It operates ride hailing in thousands of cities, a food and grocery delivery business built on the same courier network, a freight brokerage matching shippers with carriers, and an advertising business that sells placement inside those apps. Listed on the New York Stock Exchange since 2019, the company reached sustained profitability in the mid 2020s and now partners with autonomous vehicle developers rather than building self-driving technology itself.

About the role and team

Operating across key business areas like grocery and food, the Consumer Incentives team drives Uber's growth and long-term profitability. We deliver products that create seamless, affordable, and enjoyable customer experiences by building AI/ML-powered intelligence and sophisticated distributed systems at scale for hundreds of millions of global users.

What you’ll do

As a Senior Staff Machine Learning Engineer, you will shape the technical vision and long-term ML strategy for Consumer Incentives. You will tackle fundamental questions about how to personalize incentives, understand their incremental impact on consumer behavior, and optimize investment to deliver customer value and sustainable business growth.

This is a hands-on technical leadership role spanning machine learning, optimization, experimentation, and large-scale systems. You will lead initiatives across team boundaries, partner with engineering and cross-functional leaders to define the roadmap, and translate advances in ML into reliable products with measurable business impact. Building on our established capabilities in deep learning and constrained optimization, you will also help identify and develop opportunities for reinforcement learning, foundation models, and generative AI.

  • Set technical direction: Define the long-term ML vision, architecture, and technical roadmap for Consumer Incentives, aligning investments with consumer needs and business priorities.
  • Lead strategically important initiatives: Turn ambiguous problems into actionable technical strategies, and drive execution across teams from problem formulation and offline evaluation through experimentation, production deployment, and ongoing improvement.
  • Advance personalization and optimization: Design models and algorithms that improve incentive relevance, estimate incremental impact, and optimize decisions under business and operational constraints.
  • Architect scalable ML systems: Guide-and contribute directly to-the design and implementation of end-to-end ML systems, spanning data and feature pipelines, model training, inference, and monitoring, with a high bar for reliability, scalability, and maintainability.
  • Connect scientific rigor to business outcomes: Establish strong approaches to model evaluation, experimental design, and causal measurement, balancing short-term results with long-term consumer value and sustainable growth.
  • Translate emerging techniques into practical advances: Evaluate where reinforcement learning, foundation models, and generative AI can meaningfully improve our products, and lead promising approaches from exploration to production.
  • Build alignment across functions: Partner with product management, data science, operations, and engineering leaders to prioritize opportunities, make technical tradeoffs, and deliver shared outcomes.
  • Multiply the impact of others: Mentor engineers and technical leaders, raise the quality of technical decision-making, and build reusable capabilities that accelerate work across teams.

Basic Qualifications

  • Masters degree or Ph.D in Computer Science, Engineering, Mathematics
  • 12+ years of ML experience, including significant work on large-scale deep learning systems.
  • Demonstrated ownership of high-impact ML systems such as search, recommendations, personalization, targeting.
  • Proven ability to set the technical strategy for a large organization and influence product roadmaps at the executive level.
  • Strong product intuition and ability to connect model improvements to business outcomes.

Preferred Qualifications

  • Track record of successfully launching multi-year, multi-org ML initiatives that drove step-change business outcomes.
  • Successfully championed and driven the adoption of multi-year technical roadmaps across multiple large engineering organizations.
  • Elevated engineering standards through mentorship and technical leadership, establishing org-wide best practices.

For New York City, NY-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 per year.

For San Francisco, CA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 per year.

For Seattle, WA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 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.

Free account
Stop reading job ads. Get the ones that fit.
One free account turns this page into a shortlist built around your stack, your level and your pay.
Match on every job. Stack, seniority, pay and location, scored against your profile.
2,078,996 open roles. Read straight off company career pages, refreshed every day.
Unlimited applications. Every one you send is tracked in one place, on-site or on a company board.
3 tailored CVs a month. Rewritten for the exact job you are applying to. Included free.
Create a free account Continue with Google
Free forever. No card. Under a minute.

Your match

How well do you fit this role?
Two answers are enough for a real match. No account needed.
Check my fit
Answers stay in this browser until you create an account.

Recommended for you based on this role

AI/ML
Similar stack
Same company
San Francisco
$180k – $190k per year · In office · Public Trust · 5+ years exp · Bachelor's Degree · United States
Python
Python
pySpark
Pydantic
Databases
Databricks
Delta Lake
AI/ML
Copilot
Cursor
Spark
Claude Code
LoRA
MLFlow
Vertex AI
Fine-tuning
Function Calling
PEFT
AWS Bedrock
PyTorch
LLM
RAG
OpenAI
Amazon SageMaker
OpenAI Codex
OCR
Structured Outputs
Machine Learning
DevOps
GCP
Azure
AWS
VPN
Apply
$107k – $179k per year · In office · TS/SCI · Part-Time · 8+ years exp · Bachelor's Degree · Washington
Python
SQL
AI/ML
LangChain
RAG
Machine Learning
DevOps
GCP
Azure
CI/CD
AWS
Apply
$100k – $200k per year · In office · TS/SCI · 10+ years exp · Bachelor's Degree · Columbia
AI/ML
Embeddings
LLM
Tokenization
Machine Learning
Apply
In office · Full-Time · 6+ years exp · Bachelor's Degree · Los Angeles
Python
AI/ML
Fine-tuning
Quantization
Knowledge Distillation
TensorFlow
PyTorch
Anomaly Detection
Recommender Systems
Model Distillation
Machine Learning
Analytics
A/B Testing
Apply
In office · Full-Time · 8+ years exp · Bachelor's Degree · Santa Clara
AI/ML
AI Agents
LocalAI
DevOps
Linux
Windows
Apply
In office · Full-Time · San Francisco · Zurich
Python
AI/ML
Reinforcement Learning
Multimodal AI
Knowledge Distillation
VLM
PyTorch
Self-Supervised Learning
Post-training
Pre-training
Vision-Language-Action
World Models
Model Distillation
Robotics
Teleoperation
Imitation Learning
Reinforcement Learning
Apply
In office · 6+ years exp · Bachelor's Degree · San Francisco
Python
Java
C++
DevOps
GCP
Cybersecurity
HIPAA
FedRAMP
Apply
≈ $214k – $414k per year (Estimated) · In office · 4+ years exp · Bachelor's Degree · San Francisco
AI/ML
Diffusion Models
Computer Vision
NLP
Transformers
Machine Learning
Apply
$75k – $142k per year · In office · Full-Time · 2+ years exp · Bachelor's Degree · Columbia · San Francisco
AI/ML
AI Agents
Agentforce
Apply
$149k – $260k per year · In office · Full-Time · 4+ years exp · PhD · San Francisco · Washington
Python
Java
C#
C++
Databases
MySQL
PostgreSQL
AI/ML
Claude
Function Calling
AI Agents
LLM
Agentforce
DevOps
ZooKeeper
GCP
Azure
AWS
Docker
Kubernetes
TCP/IP
DNS
Cybersecurity
Threat Modeling
OWASP
Apply
See all jobs
This is one of many
2,078,996 more open roles from verified company boards, updated every day.