Staff Full Stack Engineer developing AI solutions for General Motors' intelligent driving technologies. Collaborating with machine learning engineers and research scientists to improve workflows.
Responsibilities
Build UX experiences and agentic workflows to improve MLE workflows and productivity
Build backend integrations to provide unified experience across ML lifecycle
Raise the bar on system observability, debuggability, and operational excellence, and user experience
Own and drive the design and architecture across the ecosystem that meets security and compliance standards
Establish consistent metrics to measure platform performance & health and create the roadmap for scale, reliability, low latency and speed of development and deployment
Partner with cross functional teams to understand requirements to design, architect and build framework of UX and backend integrations
Partner with engineering teams to ensure seamless end-to-end flow and data quality
Work across the project lifecycle: requirements, design, prototype, implementation, review, release, monitoring
Review and approve technical design documents and pull requests
Improve and enhance engineering systems documentation and development processes
Identify and pursue new paths of inquiry, innovation and challenge status quo
Develop and nurture technical talent within the team and recruiting
Requirements
Experience building, deploying, and operating high-availability services
Led large technical initiatives from idea to operationalization and continuous evolution of technical solution to enable new business capabilities and improve efficiencies
Ability to identify broad challenges (technical, functional, business challenges) worth tackling, and parse them into initiatives within and across engineering teams
Experience creating ground up enterprise architecture, systems architecture, integration architecture standards, frameworks, and practices
Programming experience in Python, Java, Go
Experience working with cloud infrastructure, automations, configuration management, artifact management and building advanced CI/CD solutions
Experience building production-level frontend applications using React, Angular or similar frameworks
Strong understanding of JavaScript/TypeScript and dynamic frontend fundamentals
BS, MS, or PhD in Computer Science, Math, Physics, or equivalent experience
Master Thesis focusing on developing machine learning models for lithium - ion cell sorting at Fraunhofer LBF. Involvement in innovative projects addressing circular economy in battery recycling.
Machine Learning Engineer designing and implementing AI systems focused on Japanese language challenges at Woven by Toyota. Involves technical R&D, system design, and collaboration with cross - functional teams.
Principal Software Engineer leading MLOps within Analytics Platform at Sun Life. Focused on AWS and machine learning operations, collaborating across technical and business teams.
Machine Learning Engineer designing and optimizing deep learning models for safety - critical environments at Destinus. Shaping the future of high - speed, autonomous flight technologies.
Machine Learning Engineer optimizing personalization systems for Spotify's audio streaming service. Collaborating with cross - functional teams to enhance user experience and deliver recommendations.
Principal Machine Learning Engineer developing ML and GenAI solutions in a cloud - native environment at Flexera. Leading a high - impact team and driving operational excellence for ML infrastructure.
Senior ML Platform/Ops Engineer building ML systems for AI - powered learning at Preply. Productionizing machine learning with high reliability, performance, and observability in a hybrid environment.
Senior ML Platform/Ops Engineer building AI - powered ML pipelines for a dynamic Ed - Tech company. Collaborating with ML scientists and engineers to ensure reliable deployment and observability.
Machine Learning Engineer developing advanced Deep Learning models for autonomous driving technology at Mobileye. Collaborating in a high - end algorithmic engineering team on critical computer vision challenges.