Lead Python Engineer​/MLOps; async

What we are building

Mimica's mission is to empower enterprises, teams, and individuals to reclaim their most precious resource — time and work more efficiently, with greater purpose and impact.

Our AI-powered task mining observes employee actions across the desktop and categorizes them into detailed process maps. Mimica’s process intelligence highlights inefficiencies, prioritizes improvements based on ROI, recommends the optimal technology for automation (RPA, intelligent document processing, GenAI), and provides a blueprint for building new automations and transforming work.

In this role, you will own and support the development of our data orchestration and processing pipeline.

You will build apps and core components of our ML systems, deliver new AI features and drive improvements to our infrastructure and services.

You will join the Data Intelligence Team
, whose goal is to provide ML-enriched data for downstream tasks and ensure user data privacy. You‘ll have the opportunity to shape our technical direction, architecture processes and culture.

• Write Python applications that are resilient, robust, and integrate well with other apps in a service architecture.

• Furthering Developer Experience (Dev Ex) by mentoring others in writing code that is intuitive, clear, and easy to test

• Developing observability for new and existing ML applications and GenAI/LLM integrations
  , making use of the Grafana Stack (Prometheus, Loki, Tempo)

• Develop integrations and services that communicate with Google Services.

• Working closely with Data Scientists and ML Engineers throughout the lifecycle of product ionising their models

• Being responsive to incidents regarding ML applications - including an understanding of how to triage and resolve issues relating to CPU, memory, and GPU utilisation

• Documenting procedures and guides to facilitate knowledge sharing and help other engineers 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.

• Strong proficiency with Python and Backend-Engineering

• Experience owning projects from start to finish, including speccing, architecture, development, testing, deployment, release and monitoring

• Strong skills in building maintainable tests, observability and tracing systems.

• Knowledge of best practices for performance optimisation, memory management.

• Familiarity with Kubernetes
  , Docker and other cloud infrastructure, ops and containerised tools.

• 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.

• Having been a founding/early member of an Engineering team

• Experience working within a fast-growing Scale-up environment – delivering value quickly and iteratively

• Experience with GCP

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.

💰 Generous compensation + stock options - aligned with our internal framework, market data, and individual skills.

🏢 Distributed work:
Work from anywhere - fully remote, in our hubs, or a mix.

💻 Company-issued laptop*, remote setup stipend, and co-working budget

📍 Flexible schedules and location

☀️ Ample paid time off, in addition to local public holidays

🍼 Enhanced parental leave

🧘♀️ Health & retirement benefits

📖 Annual learning & development budget - up to £500 / €600 / $650 per year

🌴 Annual workaways and regular virtual & in-person socials

🌍 Opportunity to contribute to groundbreaking projects that shape the future of work

Note:

Some benefits may vary depending on location and role

On company equipment:
Company-issued equipment (e.g. laptops) is provided for work use and must be returned upon departure, unless otherwise agreed.