Senior Machine Learning Engineer
HybridAustin, Texas, United States
Job Summary
Build a first-class machine learning platform from the ground up that manages the entire model lifecycle, including feature engineering, training, versioning, deployment, and online serving. Apply expertise to identify and generate features for multiple use cases while developing algorithms using decision trees, neural networks, and Bayesian analysis to improve product performance and accuracy. Conduct low-level systems debugging and performance optimization on large production clusters for batch and real-time prediction scenarios. Partner with product managers, data scientists, and engineers to deliver solutions for ad relevance, yield optimization, and demographic inference. Continuously adapt to emerging technologies and industry trends within the advertising ecosystem.
Required Qualifications
- Bachelors, Masters, or PhD in Computer Science, Statistics, or a related field
- 5 years of experience in applied machine learning on real use cases
- Proficient coding skills and strong software development experience in Spark, Python, or Java
- Familiarity with real-time evaluation of models with low latency constraints
- Familiarity with distributed ML frameworks such as Spark-MLlib, TensorFlow, etc.
- Ability to work with large scale computing frameworks, data analysis systems, and modelling environments i.e. Spark, Hive, NoSQL stores such as Aerospike and ScyllaDB
- Knowledge of experimental methodologies
- Knowledge of statistics
- Knowledge of optimization
- Knowledge of probability theory
- Knowledge of machine learning
- Experience with Decision Trees
- Experience with Logistic Regression
- Experience with Neural Networks
- Experience with Bayesian Analysis
Desired Qualifications
- Ad Tech experience is preferred
- Proficient use of AI tools and agentic coding practices
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.