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We are seeking an experienced software engineering lead for the Everseen ML Operations department. You and your team will extend the capabilities of our scalable ML Ops infrastructure that empowers our data scientists and machine learning engineers to develop, train, benchmark, and monitor our machine learning models efficiently. You will be instrumental in enhancing our internal Machine Learning Platform and driving automation, reproducibility, and performance across the machine learning lifecycle.
Job Responsibility:
Manages and leads the team reporting to them
Manage the day-to-day running of the team and the projects
Has overall responsibility for the projects that the team is working on
Acts as a point of escalation for the team
Working with senior leadership to create strategic goals for their team
Measures performance of those goals
Monitors and supports team members' career paths
Evaluate team members' performance and propose promotions
Assesses and proposes team headcount adjustments based on the project roadmap and team capacity
Ensures the sharing of skills, knowledge, and expertise between members of the engineering team
Fosters a culture of collaboration and continuous learning by organizing training sessions, workshops, and knowledge-sharing sessions
Coordinates and drive progress with cross-functional teams in designing and developing new features and functionalities
Ensures that the developed solutions meet project objectives and enhance user experience
Ensures design and implementation of reusable, testable, efficient, and elegant code based on requirements and a longer-term product and feature strategy
Ensures adherence to coding standards and best practices
Ensures the evaluation, integration, and maintenance of third-party software solutions to optimize system performance
Ensures expansion of product capabilities by integrating compatible third-party solutions
Ensures seamless operation and timely resolution of any anomalies to maintain system reliability
Responsible for ensuring that documentation is clear, comprehensive, and up-to-date while overseeing its creation, maintenance, and adherence to organizational standards
Requirements:
5+ years of experience in either ML infrastructure, MLOps, or Platform Engineering