Senior Data/MLOps Engineer
Skills
Computer VisionData PipelinesDeep LearningImage ProcessingMachine LearningNatural Language ProcessingPython
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Background in solving complex technical challenges at the intersection of Computer Science, Software Development, and Data/ML Engineering
- Proficiency with Python and a desire to work with various technologies such as MongoDB to build scalable AI/ML production systems
- Experience in designing, building, and maintaining data collection tools, caching/storage systems, and pipelines
- Knowledge of best practices for performance optimization, memory management, model scalability, data storage and quality tuning
- Strong analytical and troubleshooting skills
- Drive to continually develop your skills, improve team processes and reduce technical debt
- Fluency in English and ability to effectively communicate abstract ideas, complex concepts and trade-offs
Nice to have
- Familiarity with cloud infrastructure and containerised tools
- Experience owning projects from start to finish
- Experience working within a high-impact, high-ambiguity startup environment
Day to day
- You will own the backend of our workflow mapping product, consisting of a database containing raw clicks and keystroke data, a web app where users label data, and machine learning scripts.
- You will build pipelines and core components of our ML systems, deliver new AI features and drive improvements to our infrastructure and services.
- As a founding member of our engineering team, you'll have the opportunity to shape our technical direction, processes and culture.
Hiring process
- We’d love to hear from you, even if you feel you don’t quite have all of the above