Overview
On Site
Full Time
Skills
Sage
Enterprise Search
Productivity
Sales
Semantic Search
Emerging Technologies
Open Source
SaaS
Software Engineering
FOCUS
Python
Java
C++
Shipping
Natural Language Processing
Computer Science
Machine Learning (ML)
Large Language Models (LLMs)
PyTorch
TensorFlow
Vector Databases
Machine Learning Operations (ML Ops)
Lifecycle Management
Docker
Kubernetes
Mentorship
Artificial Intelligence
Law
Legal
Collaboration
Job Details
About the Role
You will be joining AI Experience Team in Uber as a Senior Software Engineer. The AI Experience team builds the AI-powered tools and platforms that redefine productivity at Uber. We directly empower our internal teams by shipping innovative solutions that make their work faster, smarter, and more impactful. We leverage the latest advancements in AI/ML to transform core experiences for all employees.
What we do:
1. Build for Sales Efficiency: We create ML-driven solutions that provide our Sales teams with a competitive edge, from intelligent content recommendations to predictive lead scoring.
2. Develop First-Party AI Tools: We own the end-to-end development of flagship internal products like \"IT Sage\" and \"HR Sage\" (our internal conversational AI bots) and our next-generation enterprise search platform.
3. Integrate Cutting-Edge Technology: We identify, evaluate, and integrate industry-leading AI/ML SaaS solutions, ensuring Uber employees have access to the best tools on the market.
4. Champion AI Adoption: We act as internal consultants and pioneers, exposing teams across Uber to the transformative potential of new AI technologies and helping them integrate these tools into their daily work.
What the Candidate Will Do
1. Design, build, and deploy scalable, end-to-end AI/ML solutions that directly impact employee productivity and sales effectiveness.
2. Collaborate closely with product managers, designers, and business stakeholders to identify high-impact opportunities for AI integration.
3. Fine-tune and leverage foundational models (LLMs) to build sophisticated applications like conversational agents, semantic search systems, and content generation tools.
4. Develop robust data pipelines and MLOps practices to ensure our models are reliable, performant, and continuously improving.
5. Evaluate new and emerging technologies, from open-source models to third-party SaaS platforms, to determine the best path forward for Uber.
6. Write high-quality, production-ready code and contribute to a culture of engineering excellence through code reviews and mentorship.
Basic Qualifications
1. Bachelor's degree in Computer Science, Machine Learning, a related technical field, or equivalent practical experience.
2. 5+ years of professional experience in software engineering, with a focus on building backend systems or machine learning applications.
3. Strong programming proficiency in Python and at least one other language (e.g., Go, Java, C++).
4. Demonstrated experience in building and shipping products or systems that leverage machine learning, particularly in areas like Natural Language Processing (NLP), Search, or Recommender Systems.
5. Experience with the design and architecture of scalable, distributed systems.
Preferred Qualifications
1. Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
2. 6+ years of relevant industry experience.
3. Hands-on experience building applications with Large Language Models (LLMs) using frameworks like PyTorch or TensorFlow and libraries like Hugging Face Transformers.
4. Proven experience with Retrieval-Augmented Generation (RAG) architectures and familiarity with vector databases (e.g., Pinecone, Weaviate, Milvus).
5. Experience with MLOps principles and tools for model deployment, monitoring, and lifecycle management (e.g., Docker, Kubernetes, Kubeflow, MLflow).
6. Experience leading complex technical projects, including mentoring junior engineers and driving engineering excellence within a team.
7. A strong product sense and a passion for creating user-centric AI experiences that solve real-world problems.
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.
You will be joining AI Experience Team in Uber as a Senior Software Engineer. The AI Experience team builds the AI-powered tools and platforms that redefine productivity at Uber. We directly empower our internal teams by shipping innovative solutions that make their work faster, smarter, and more impactful. We leverage the latest advancements in AI/ML to transform core experiences for all employees.
What we do:
1. Build for Sales Efficiency: We create ML-driven solutions that provide our Sales teams with a competitive edge, from intelligent content recommendations to predictive lead scoring.
2. Develop First-Party AI Tools: We own the end-to-end development of flagship internal products like \"IT Sage\" and \"HR Sage\" (our internal conversational AI bots) and our next-generation enterprise search platform.
3. Integrate Cutting-Edge Technology: We identify, evaluate, and integrate industry-leading AI/ML SaaS solutions, ensuring Uber employees have access to the best tools on the market.
4. Champion AI Adoption: We act as internal consultants and pioneers, exposing teams across Uber to the transformative potential of new AI technologies and helping them integrate these tools into their daily work.
What the Candidate Will Do
1. Design, build, and deploy scalable, end-to-end AI/ML solutions that directly impact employee productivity and sales effectiveness.
2. Collaborate closely with product managers, designers, and business stakeholders to identify high-impact opportunities for AI integration.
3. Fine-tune and leverage foundational models (LLMs) to build sophisticated applications like conversational agents, semantic search systems, and content generation tools.
4. Develop robust data pipelines and MLOps practices to ensure our models are reliable, performant, and continuously improving.
5. Evaluate new and emerging technologies, from open-source models to third-party SaaS platforms, to determine the best path forward for Uber.
6. Write high-quality, production-ready code and contribute to a culture of engineering excellence through code reviews and mentorship.
Basic Qualifications
1. Bachelor's degree in Computer Science, Machine Learning, a related technical field, or equivalent practical experience.
2. 5+ years of professional experience in software engineering, with a focus on building backend systems or machine learning applications.
3. Strong programming proficiency in Python and at least one other language (e.g., Go, Java, C++).
4. Demonstrated experience in building and shipping products or systems that leverage machine learning, particularly in areas like Natural Language Processing (NLP), Search, or Recommender Systems.
5. Experience with the design and architecture of scalable, distributed systems.
Preferred Qualifications
1. Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
2. 6+ years of relevant industry experience.
3. Hands-on experience building applications with Large Language Models (LLMs) using frameworks like PyTorch or TensorFlow and libraries like Hugging Face Transformers.
4. Proven experience with Retrieval-Augmented Generation (RAG) architectures and familiarity with vector databases (e.g., Pinecone, Weaviate, Milvus).
5. Experience with MLOps principles and tools for model deployment, monitoring, and lifecycle management (e.g., Docker, Kubernetes, Kubeflow, MLflow).
6. Experience leading complex technical projects, including mentoring junior engineers and driving engineering excellence within a team.
7. A strong product sense and a passion for creating user-centric AI experiences that solve real-world problems.
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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.