Duties and Responsibilities
Design and define enterprise framework, toolsets, standards and integration mechanisms to ensure portability and consistency of models and configuration:
- Work closely with Research Data Scientist and Product Owner to continuously evaluate and recommend best in class technologies for implementation into our Machine Learning Platform
- Create architecture and process for operationalizing and productionalizing the models
- Create architecture for automating ML workloads
- Create architecture for Machine Learning Operations (MLOps)
- Define the model management system, technologies, and processes to manage model development, training, and deployment including hyper-parameter configuration and optimization.
- Collaborate with operations teams to define an automated compute and I/O provisioning platform to democratize access to compute resources.
Define the model migration process, standards for hyper-parameter management, model testing and metrics generation:
- Partner with DevOps and operations teams to determine system configuration
- Define the framework to ensure that the model and hyper-parameter changes during testing and training are stored and synchronized with build and eventually inference environment.
Define monitoring framework for performance and model decay, and collaborate with data scientist and operations teams for review of metrics data.
Additional responsibilities include:
1. Provides the architectural leadership in shaping strategic, business technology programs, with an emphasis on application architecture. Utilizes domain knowledge and application portfolio knowledge to play a key role in defining the future state of large, business technology programs.
2. Utilizes broad and deep understanding of the competitive landscape and corporate and business unit strategies to provide context for architectural decision making.
3. Within area of responsibility, continuously pursues advanced knowledge of business technology solutions and maintains understanding of applicable technologies, tools, and services:
- Establishes working relationships with appropriate business technology solution providers (e.g., Domino Data Lab, Amazon Web Services, etc.).
- Leverages knowledge capital available through subscription research services that target business technology solutions (e.g., Forester, Gartner, etc.).
- Leverages the Internet and trade periodicals that focus on the contemporary, competitive, business technology issues within the financial industry.
- Attends financial industry conferences and engages in associated activities (e.g., conducting presentations, leading workshops, etc.).
4. Defines reference and implementation application architectures.
5. Produces technology roadmaps in support of SI’s application portfolio vision and strategy.
6. Monitors application implementation activity to ensure architecture and design principles are upheld.
7. Ensures application implementation solutions support the business objectives (asset gathering, cost optimization, client loyalty improvement), as appropriate.
8. Participates in governance team discussions and provides a strong voice on critical decisions.
9. Establishes relationships with senior IT and Business leaders for the purpose of advancing proposed application architecture solutions.
10. Coaches and mentors more junior solution architects.
11. Participates in special projects and performs other duties as assigned.
- Back end web-services: Python, Java, Flask, Django, Kubernetes, Docker, Design RESTful APIs, Microservices.
- Machine Learning: TensorFlow, Keras, Apache MXNet, Torch, Theano
- Familiarity with ML libraries, such as scikit-learn, caret, mlr, mllib
- ML Technologies: NLP, Computer Vision, Model Management
- Experience with Big Data technologies: Kafka, Apache Spark, Hadoop, Hive, Presto
- Deep understanding of Cloud databases (RDS/AWS preferred), networking, serverless infrastructure
- Experience in defining, deploying, and scalaing APIs
- Solid Experience architecting and developing AI and machine learning applications
- Experience with full stack applications with AWS platform is a big plus
- Strong Communication and Presentation skills
Experience / Qualifications
- 3 or more years Architecture
- 5 or more years Software Development
- 3 or more years Cloud Architecture / DevOps
- 3 or more years AI/ML Engineering
- Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred.
- Minimum eight years relevant work experience.
Vanguard is not offering visa sponsorship for this position.
We are Vanguard. Together, we’re changing the way the world invests.
For us, investing doesn’t just end in value. It starts with values. Because when you invest with courage, when you invest with clarity, and when you invest with care, you can get so much more in return. We invest with purpose – and that’s how we’ve become a global market leader. Here, we grow by doing the right thing for the people we serve. And so can you.
We want to make success accessible to everyone. This is our opportunity. Let’s make it count.
Vanguard’s continued commitment to diversity and inclusion is firmly rooted in our culture. Every decision we make to best serve our clients, crew (internally employees are referred to as crew), and communities is guided by one simple statement: “Do the right thing.”
We believe that a critical aspect of doing the right thing requires building diverse, inclusive, and highly effective teams of individuals who are as unique as the clients they serve. We empower our crew to contribute their distinct strengths to achieving Vanguard’s core purpose through our values.
When all crew members feel valued and included, our ability to collaborate and innovate is amplified, and we are united in delivering on Vanguard’s core purpose.
Our core purpose: To take a stand for all investors, to treat them fairly, and to give them the best chance for investment success.
To apply for this job please visit www.vanguardjobs.com.
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