Uber Machine Learning Engineer - Applied AI 

United States, West Virginia 

185117852

About the Role

- - - - What the Candidate Will Do ----

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

- - - - Basic Qualifications ----

1. PhD or equivalent in Computer Science, Engineering, Mathematics or related field AND 2-years full-time Software Engineering work experience OR 5-years full-time Software Engineering work experience, WHICH INCLUDES 3-years total technical software engineering experience in one or more of the following areas:
2. Programming language (e.g. C, C++, Java, Python, or Go)
3. Large-scale training using data structures and algorithms
4. Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning)
5. Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib
6. Note the 3-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.
7. Experience with ML packages such as Tensorflow, PyTorch, JAX, and Scikit-Learn.
8. Experience with big-data architecture, ETL frameworks such as Spark, MapReduce, HDFS, Hive.

- - - - Preferred Qualifications ----

1. 3+ years of experience in the development, training, productionization and monitoring of ML solutions at scale.
2. Experience with formulating a business problem as an ML problem, identifying the right features, model structure and optimization constraints, and delivering business impact.
3. Experience in modern deep learning architectures and recommender systems.
4. Experience in building foundational data and embeddings that can be plugged into other application specific models.
5. Experience working with multiple across team and org boundaries with engineering and product counterparts.

For San Francisco, CA-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.