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
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
- Advanced experience in Python and distributed computing frameworks such as PySpark
- Experience in setting up Machine Learning platform infrastructure and deploying to the cloud to develop and train machine learning models
- Hands-on experience and solid understanding of machine learning methods and MLOps, deploying and scaling ML and AI Models on Public cloud services
- Hands-on experience with AWS cloud-based application development and infrastructure - EC2,EMR, EKS
- Experience in designing and building AWS data pipelines using Lambda, SQS, SNS, Athena, Glue, EMR, S3 to facilitate ML training
- Analyzing and evaluating the ongoing performance of developed models
- Overall knowledge of the Model Development Life
- AWS cost monitoring and optimization, S3 lifecycle policy, Data archival and retention,
Preferred qualifications, capabilities, and skills
- Familiarity with ML algorithms - Xgboost, CNN, RNN