State Street's Artificial Intelligence and Financial Engineering is a global award-winning team. It has the mission to explore, enable and exploit artificial intelligence, machine learning, natural language processing, image recognition and cognitive computing at scale for countless use cases across Alpha/CRD, Global Services, Global Advisors, Global Markets, and corporate functions. The team has a mixed of intelligence technology, quantitative modeling, data science, financial engineering, and software engineering capabilities. The team has solved operational, and client experience related use cases and is making into investment and risk management related domains such as market movement, sentiment analysis, valuation, investment strategy, fund innovation and so on. This team has engaged the business to explore, prototype, and solution use cases while also building out a portfolio of foundational micro services and products in the State Street's public cloud.
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The AI/ML Software Engineering - Vice President will work with other AIFE agile team members through the phases of use-case data exploration and prototyping to the design, implementation and support deployment of the resulting AI services while focusing on IT implementation.
Responsibilities:
- Responsible for IT technology evaluation, architecture, POC, and implementation to ensure resiliency, scalability, and system performance of implemented solution and platform.
- Lead and mentor a team of software engineers through design, coding, unit test, integration, QA/UAT, and production rollout while very hands-on coding on daily basis.
- Design solution architecture, perform hardware capacity/cost optimization, define technology roadmap and platform deployment strategy, and optimize software development environment like source code management and CI/CD pipelines.
- Work with AI/ML scientists and other team members to provide end to end solution to solve real-world problems for both internal and external customers.
- Responsible for IT maintenance and support for production solutions and platforms.
- Communicate with business and technology stakeholders in a global setting.
Qualifications:
- Master degree required in computer science or relevant engineering field.
- Extensive experience in delivering commercialized software product with robust architecture and modern tech stacks.
- Familiar with cloud native technologies in Azure or AWS such as computing, storage, distributed computing, parallel processing, containerization, schedulers, messaging, security, micro service, and data management/pipelines.
- 12+ years of enterprise Java and 5+ years of Python programming and design experience
- 8+ years of development experience with cloud data platforms like Snowflake, Databricks or Spark
- 5+ years of development experience with messaging queue like Kafka and Service Bus
- 5+ years of experience in automation and building deployment pipelines based on Azure DevOps, Github, YAML, Terraform/Terragrunt, and Maven
- 5+ years of working experience with Machine Learning Frameworks (TensorFlow, PyTorch, Apache Spark / MLlib, etc.) and AI platform such as Azure Machine Learning and AWS SageMaker.
- Result driven, detail oriented, candid attitude
Experience in any of the following is highly desirable:
- Architecture experience with industry leading software platform on public cloud for revenue generation.
- Data Science and Machine Learning Frameworks (TensorFlow, PyTorch, Scikit-learn,etc.)
- Linux / Bash scripting, structured and unstructured data management tools (Snowflake, Data brick, Graph DB, PostgreSQL, etc.)
- Prior working experience with asset management industry and basic capital market knowledge e.g. passed Charted Financial Analyst (CFA) level 1 exam.
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