As a Front End Engineer (full stack engineers welcome), you will play a pivotal role in supporting tech leadership by participating in the design, development, and testing of software, creating user interactions and wireframes for web applications. You will participate in the UX and UI design of key ML initiatives, ensuring their successful integration into SynthBee’s infrastructure and applications. This role requires a strong foundation in agile software system development and front-end and familiarity with back-end development, ensuring reliability, and aligning systems with business goals. You’ll collaborate with cross-functional teams to drive innovation and support the seamless operation of ML-powered applications.
Software Development
Experience building and advocating strong CI/CD strategies including deployment automation, testing strategies, automation tools, and processes meant to improve the software development lifecycle. Assist in the design, and architecture of new software solutions to fulfill project requirements.
Continuous Integration Systems
Runs and operates continuous integration systems like GitHub, Jenkins, CircleCI, Azure DevOps, AWS CodePipeline, and others.
Performance Testing
Design testing strategy in partnership with cross-functional partners to monitor performance and ensure robust and secure deployment practices to enhance system reliability and scalability.
Collaboration and Alignment
Partner with the VP of Software Systems and other engineering teams to develop ML systems that align with business objectives and user needs. Facilitate cross-functional collaboration to ensure the successful delivery of ML initiatives.
Documentation and Knowledge Sharing
Develop and maintain detailed documentation for ML systems, pipelines, and processes to ensure reproducibility and clarity. Contribute to the team’s technical growth by sharing insights, providing mentorship to junior team members, and fostering a collaborative environment.
Continuous Learning and Innovation
Stay updated on front-end and back end web application technologies and framewords, databases, and other technological tools.
Risk and Compliance Management
Ensure ML systems comply with security and regulatory standards, particularly in handling sensitive data and critical applications.