Uber Sr Software Engineer - Machine Learning Semantic Data Team 

United States, West Virginia 

868553329

What You'll Do

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

Basic Qualifications

• PhD or equivalent in Computer Science, Engineering, Mathematics or related field OR 3-years full-time Software Engineering work experience, WHICH INCLUDES 2-years total technical software engineering experience in one or more of the following areas:
  • Programming language (e.g. C, C++, Java, Python, or Go)
  • Training using data structures and algorithms
  • Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning)
  • Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib
• Note the 2-years total of specialized software engineering experience may have been gained through education and full-time work experience, additional training, coursework, research, or similar (OR some combination of these). The years of specialized experience are not necessarily in addition to the years of Education & full-time work experience indicated.
• Experience working with multiple across team and org boundaries with engineering and product counterparts.
• Experience with big-data architecture, ETL frameworks such as Spark, MapReduce, HDFS, Hive.

Preferred Qualifications

• 4+ years of experience working on building ML models, iterating on them, and shipping them to production them.
• Experience with taking on vague business problems, formulation them as ML problems, identifying the right features, model structure and optimization constraints, and delivering business impact.
• Experience in building foundational data and embeddings that can be plugged into other application specific models.
• Experience in optimize Spark queries for better CPU and memory efficiency.
• Experience in working with models for personalization use cases.

For San Francisco, CA-based roles: The base salary range for this role is USD$185,000 per year - USD$205,500 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$185,000 per year - USD$205,500 per year.