Senior/Lead MLOps Engineer, Mimica

• Background in solving complex technical challenges at the intersection of Software Development, and Data/ML Engineering
• Proficiency with Python and databases in high scale environments
• Hands-on experience with message queues like RabbitMQ, NATS, gRPC, REST or others
• Familiarity with cloud infrastructure, ops and containerised tools like K8s, Docker or others
• Experience in designing, building, and maintaining data collection tools, caching/storage systems, queues and pipelines
• Knowledge of best practices for performance optimization, memory management, model scalability, as well as data storage and quality tuning
• Strong analytical and troubleshooting skills – methodically decomposing systems to identify bottlenecks, determine root causes, and implement effective solutions
• 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

Desirable

• In this role, you will own the backend of our new Product - the Mimica Maker
• This will be a product that allows users to build and orchestrate bots from the data we record
• You will build pipelines and core components of our ML systems, deliver new AI features and drive improvements to our infrastructure and services
• As an early member of the MLOps Chapter, and a founding member of the Maker Team, you‘ll have the opportunity to shape our technical direction, processes and culture
• Writing algorithms to process complex data structures
• Developing data and ML training pipelines (dataset creation, model training, and evaluation)
• Working closely with Data Scientists and ML Engineers to design the architecture of our next generation of models, deploy them into production and optimize their performance
• Monitoring model deployments to anticipate and mitigate system performance issues (disk utilization, memory and CPU usage)
• Build and enhance tools for monitoring and measuring model accuracy, performance, and data quality
• Documenting procedures and guides to facilitate knowledge sharing and helping other engineers to level up through pairing and mentoring
• Participating in hiring and onboarding new team members; taking on end-to-end project management responsibilities as we grow