Machine Learning Engineer - Applied AI

$158,000 - $175,500/Yr

Uber - Sunnyvale, CA

Full-time

Sunnyvale, CA

Transit and Ground Passenger Transportation

About the position

The Applied AI team at Uber is dedicated to collaborating with various product teams to deliver innovative AI solutions that address core business challenges. This team works closely with engineering, product, and data science teams to identify significant business problems and explore the potential of AI solutions. The team is responsible for delivering these AI solutions from inception to completion. Key areas of expertise within the team include Computer Vision, ML Optimization, Geospatial AI, Personalization, and Generative AI. Within this framework, the Generative AI team focuses on building a semantic layer that enhances our understanding of entities relevant to the Uber platform, such as places, merchants, items, riders, and eaters. The team collaborates with partners across various teams to design, develop, and productionize semantic data, features, and embeddings that cater to business needs. This role involves building and iterating on capturing semantic information of Uber entities by leveraging large language models (LLMs) and generating embeddings that improve our understanding of these entities. The ultimate goal is to leverage this information to enhance machine learning models across Uber and create novel personalized experiences for users.

Responsibilities

• Build and iterate on capturing semantic information of Uber entities by leveraging LLMs.
• Generate embeddings using the semantic information to improve understanding of places, merchants, items, and users.
• Leverage semantic information to enhance ML models across Uber and develop personalized experiences.

Requirements

• PhD or equivalent in Computer Science, Engineering, Mathematics, or related field AND 2 years of full-time Software Engineering work experience OR 5 years of full-time Software Engineering work experience, which includes 3 years of technical software engineering experience in programming languages (e.g., C, C++, Java, Python, or Go).
• Experience in large-scale training using data structures and algorithms.
• Proficiency in modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning).
• Experience with machine learning software such as Tensorflow, PyTorch, Caffe, Scikit-Learn, or Spark MLLib.
• Experience with ML packages such as Tensorflow, PyTorch, JAX, and Scikit-Learn.
• Experience with big-data architecture and ETL frameworks such as Spark, MapReduce, HDFS, and Hive.

Nice-to-haves

• 3+ years of experience in the development, training, productionization, and monitoring of ML solutions at scale.
• Experience in formulating business problems as ML problems, identifying the right features, model structure, and optimization constraints, and delivering business impact.
• Experience in modern deep learning architectures and recommender systems.
• Experience in building foundational data and embeddings that can be integrated into application-specific models.
• Experience working collaboratively across teams and organizational boundaries with engineering and product counterparts.

Benefits

• Participation in Uber's bonus program.
• Eligibility for equity awards and other types of compensation.
• Various health and wellness benefits as detailed on Uber's careers page.