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 components of our Machine Learning pipeline end-to-end. This means analysing and preprocessing data, implementing pipelines, researching Computer Vision and NLP literature, as well as training, validating, and deploying models to production. As a founding member of our data science team, you‘ll have the opportunity to shape our technical direction, processes and culture.
Part of your day-to-day
- Designing and productionizing new ML models for our different products
- Working with a variety of data types, from sequential clickstream data to NLP and Computer Vision
- Creating tools to measure and improve model accuracy and data quality
- Collaborating with frontend engineers to build data annotation interfaces
- Participating in architectural decisions and collaborating across teams to identify and implement product improvements
- 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 Data Science and Software Development (from exploratory analysis to shipping production code)
- Experience writing production-grade code in Python and knowledge of (or desire to learn) technologies such as MongoDB and Node.js
- Strong understanding of various ML packages and libraries
- Working knowledge of NLP approaches such as classification, named-entity recognition, and word embeddings
- Advocacy of engineering best practices with a focus on code quality, continuous delivery, automated testing, and maintainability
- 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
- Advanced degree or research background in CS, Machine Learning, Applied Sciences, or related fields
- Familiarity with relational and NoSQL databases, including MongoDB and MySQL
- 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 don’t have expert-level knowledge of the technologies we use!
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.
United Kingdom
