Description:

The Senior Data/MLOps Engineer will be responsible for the backend of the workflow mapping product, including a database with raw clicks and keystroke data, a web app for data labeling, and machine learning scripts.
They will build pipelines and core components of ML systems, deliver new AI features, and enhance infrastructure and services.
The role involves writing algorithms for processing complex data structures, developing data and ML training pipelines, and collaborating with Data Scientists and ML Engineers to design and deploy new models.
Responsibilities also include monitoring model deployments, automating deployment pipelines, documenting procedures for knowledge sharing, and participating in hiring and onboarding new team members.

Requirements:

Background in solving technical challenges at the intersection of Computer Science, Software Development, and Data/ML Engineering.
Proficiency in Python and experience with technologies like MongoDB for building scalable AI/ML production systems.
Experience in designing, building, and maintaining data collection tools, caching/storage systems, and pipelines.
Knowledge of performance optimization, memory management, model scalability, data storage, and quality tuning best practices.
Strong analytical and troubleshooting skills to identify bottlenecks and implement effective solutions.
Drive to continuously develop skills, improve team processes, and reduce technical debt.
Fluency in English with the ability to communicate abstract ideas and complex concepts effectively.

Generous compensation with a commitment to paying at the top of the local market.
Health benefits, ample paid time off, flexible schedules, and location options.
Start-to-finish project ownership and the opportunity to contribute to projects shaping the future of work.