People Matter

Senior Data/MLOps Engineer (AI-Powered Platform) - REMOTE UK/Europe/Americas

Mimica Automation

Mimica Automation

Software Engineering, Data Science
London, UK
Posted on Monday, June 24, 2024

What we are building

Mimica's mission is to accelerate the discovery and deployment of automation with AI.

Our first product, Mapper, learns patterns from employee clicks and keystrokes, identifies key steps, decisions and repetition and generates “blueprints” for automation. At the core of our ML pipeline is a technology translating noisy low-level computer actions into a clean, human-readable representation. Alongside creating process maps for automation, we've launched a companion tool, Miner, which helps enterprises identify and prioritize automation opportunities.

Our approach to engineering

  • We prioritize customer needs first
  • We work in small, project-based teams
  • We have flexibility in terms of the problems we work on
  • We own the full lifecycle of our projects
  • We avoid silos and encourage taking up tasks in new areas
  • We balance quality and velocity
  • We have a shared responsibility for our production code
  • We each set our own routine to maximize our productivity

What you will own

In this role, 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 (CV, NLP, etc.). 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.

Part of your day-to-day

  • 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 new 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)
  • Helping automate the execution of deployment pipelines to enable operational monitoring
  • 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.