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.
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, 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
Bonus
- Familiarity with cloud infrastructure and containerised tools like K8s, Docker and GCP
- Experience owning projects from start to finish, including speccing, architecture, development, testing, deployment, release and monitoring
- Experience working within a high-impact, high-ambiguity startup environment – delivering value quickly and iteratively
We’d love to hear from you, even if you feel you don’t quite have all of the above.
Location
This is a fully remote position. You can be based anywhere in the UK, Europe, or the Americas within a UTC-7 to UTC+3 timezone.
Benefits
We provide generous compensation and our goal is to always pay at the top of the local market. We take a structured approach to determining salaries and take into consideration our salary framework, market data, and candidates’ skills.
We also offer health benefits and ample paid time off, as well as a range of non-tangible benefits like flexible schedules and location, start-to-finish project ownership, and the opportunity to contribute to projects that will change the future of work.
