We're hiring an experienced Senior Software Engineer to join our growing Applied AI team.
What you will do:
Grow our AI and ML capabilities by contributing ideas and launching and completing new engineering projects.
Partner across all teams including engineers, AI scientists, researchers, designers, and product managers to bring new features into production.
Serve our customers by helping them unlock insights about their marketing efforts through our products and push the boundaries of what’s possible in marketing technology.
Contribute to the development and implementation of GNN architectures for marketing analytics.
Apply GNN techniques to unlock deeper insights from complex, interconnected marketing data.
How you will succeed:
Primary skills
Verbal and written communication: We’re dealing with complex, cutting-edge topics. That makes the ability to convey your ideas and concepts well is paramount.
Python programming: Experience delivering production-ready python programs.
Relational databases: Experience in querying, designing and optimizing relational databases such as Postgres.
Software development lifecycle management: Experience owning projects end-to-end from scoping, designing, coding, release and continuous monitoring in production environment.
Capacity planning and management: Experience with profiling methods and scalability assessment.
Data processing: Experience with data preprocessing techniques such as cleaning, transformation, normalization, and feature extraction.
Graph Theory and Algorithms: Strong understanding of graph theory concepts and algorithms.
Deep Learning Frameworks: Experience with PyTorch, PyTorch Geometric, or similar frameworks for implementing GNNs.
Secondary skills
ELT pipeline: Experience with ELT pipeline and orchestration systems such as Airflow.
Database systems: Experience working with one of more of non-SQL databases such as Druid, Elasticsearch and neo4j.
AWS: Experience deploying and managing applications on AWS.
Containerization and Virtualization: Proficiency in Docker and experience with container management and deployment.
Statistics and mathematics: Understanding of statistical concepts and methods such as statistical testing, regression analysis, time series analysis, and probability theory.
