Experienced Software Engineer - ML Infra Platform

Responsibilities

• Architecting Scalable ML Infrastructure: You will design and develop scalable, efficient, and robust machine learning infrastructure that supports the lifecycle of ML models—from data ingestion and processing to training, evaluation, and deployment. This infrastructure must be capable of handling large-scale data and complex computations with high reliability and performance
• Improving ML Operations (MLOps): You will innovate and implement best practices in MLOps to streamline the development, deployment, and monitoring of ML models. This includes automating pipelines, ensuring model reproducibility, and facilitating seamless model versioning and rollout
• Cross-Functional Collaboration: You will collaborate with product managers, data scientists, and other engineering teams to understand their needs and translate them into ML platform capabilities. This collaborative approach ensures that the ML infrastructure effectively supports product features and business objectives
• Mentorship and Leadership: You will mentor junior engineers and peers, sharing your knowledge and expertise to promote a culture of technical excellence. Your leadership will help develop the team's skills and foster innovation
• Staying Ahead of the Curve: You will keep abreast of the latest developments in machine learning, data engineering, and cloud technologies. By staying informed about industry trends and challenges, you will ensure that Plaid's ML platform remains cutting-edge and competitive

Qualifications

• 8+ years of Software Engineering Experience
• 3+ years with machine learning or developing machine learning platforms
• Strong communication and architecture skills
• Python experience and k8s experience
• Have been in the ML space as a DS / MLE or as a SWE heavily supporting them
• Have previous experience developing machine learning platforms / frameworks / infrastructure
• Strong communication and architecture skills
• Python experience and k8s experience