Bachelor’s degree or equivalent practical experience.
2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
Nice to haves:
Bachelor's, Master's, or PhD in Physics, Mathematics, Computer Science or a related quantitative field.
Familiarity with machine learning, Natural Language Processing (NLP), or generative AI and Large Language Models (LLMs).
Familiarity with building data processing pipelines with tools like Kafka, Apache Beam (Dataflow) or Spark.
Familiarity with Google Cloud Platform services (e.g., BigQuery, Google Kubernetes Engine, Pub/Sub).
Familiarity with time-series data and financial market data feeds.
What you'll be doing:
Design, develop, and deploy core components of the financial AI platform, including the orchestration engine, proprietary analytical tools, and data processing pipelines.
Build high-performance microservices for financial workflows, such as historical backtesting, Monte Carlo simulations, and risk calculations (e.g., VaR, expected shortfall etc).
Collaborate closely with Google's research teams to integrate and optimize forecasting and time-series analysis models for financial use cases.
Develop an intelligent orchestration layer using Google's latest large-scale models to interpret natural language queries and chain together the appropriate sequence of financial tools and data sources.
Engineer auditable data pipelines for ingesting and transforming a wide array of data, including real-time market feeds, alternative data (like news sentiment), and clients' proprietary datasets.