AWS ML Developer
- Charlotte, NC Dallas, TX
- Permanent
- Full-time
Provides senior level system analysis, design, development, and implementation of
applications and databases. Integrates third party products.
Translates technical specifications into code for complex new or enhancement
projects for internal clients. Writes programs, develops code, tests artifacts, and
produces reports. Employs software development techniques to ensure tests are
implemented in a way that supports automation.
Elevates code into the development, test, and production environments on schedule.
Provides follow up production support. Submits change control requests and
documents.
Thoroughly understands software development methodology. Thoroughly understands
development architecture standards.
Trains and mentors' staff with less experience. Resolves elevated issues.
Participates in design, code, and test inspections throughout the life cycle to identify
issues. Explains technical considerations at related meetings, including those with
internal clients. Performs systems analysis activities.
Thoroughly understands client business functions and technology needs. Has a broad
understanding of Vanguard's technologies, tools, and applications, including those that
interface with business areas and systems.
Interfaces with cross functional team members and communicates systems issues at
the appropriate technical level for each audience.
Thoroughly understands and complies with Information Technology and Information
Security policies and procedures and verifies that deliverables meet requirements.
Qualification:
10+ years of industry experience
Hands-on knowledge of Vanguard's AWS services, with experience and awareness of
features such as Lambda, DynamoDB, S3, Glue, IAM, CloudFormation, and other
AWS services.
Strong proficiency in Python coding and development skills, including unit testing
and end-to-end testing.
Proficient in JavaScript and React UI development.
Experience in API development.
Role Overview:
The role centers on AWS and Python development, with a strong back-end focus.
While some front-end work in React is expected, it is secondary. The position also
includes exposure to AI/ML technologies, supporting the build of an internal virtual
advisor platform (similar to a ChatGPT-style copilot for financial queries).Ideal Candidate Profile:
Strong AWS and Python development experience
Familiarity with AI/ML lifecycle (data prep, training, deployment, monitoring)
Model Development Lifecycle stages: Data Preparation, Training, Evaluation,
Hosting and Monitoring
AI/ML Concepts: Supervised learning, unsupervised learning, deep learning, and
model evaluation techniques
Model Development Lifecycle stages: Data Preparation, Training, Evaluation,
Hosting and Monitoring
AI/ML Concepts: Supervised learning, unsupervised learning, deep learning, and
model evaluation techniques