Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Adds to team culture of diversity, equity, inclusion, and respect
- Understands latest advancements in Python programming and machine learning techniques, and explore their potential applications within the organization.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Expertise in advanced Python programming concepts, including object-oriented programming, decorators, generators, and context managers
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Proficiency in coding in Python, with a focus on machine learning libraries and frameworks
- Overall knowledge of the Software Development Life Cycle
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc
- Experience in machine learning model development, including data preprocessing, feature engineering, model selection, training, and evaluation
Preferred qualifications, capabilities, and skills
- Familiarity with AI/ML implementation in cloud platforms, such as AWS or Azure
- Knowledge of AI/ML deployment techniques, including model serving, containerization, and cloud-based deployment
- Familiarity with agile methodologies and practices
- Desire to learn and grow within the field of advanced Python programming and machine learning