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.
What You Will Own
We're looking to improve the backend infrastructure of our AI products. This includes maintaining and improving our data processing pipelines, improving observability, building tools to support machine learning engineers (MLEs), and writing production-ready code for data preparation and processing.
You will focus on building scalable systems that enable efficient experimentation, robust data handling, and streamlined deployment of production tools. As a key member of our engineering team, you will contribute to shaping the technical direction, processes, and culture of the organization.
Part of Your Day-to-Day
- Developing robust data pipelines and tools for efficient data processing and preparation to support MLEs.
- Writing production code to implement algorithms and data transformation rules.
- Collaborating closely with MLEs, MLOps and Platform engineers to deploy production-ready models.
- Improve the observability and testing frameworks for production data pipelines and deployed models.
- Writing automated tests for data pipelines to ensure reliability and maintainability.
- Participating in simple exploratory work and experimentation, including tasks such as prompt engineering for GenAI tools and basic ML model experimentation.
- Implementing efficient and scalable data processing workflow and tools to enable researchers.
- Enhancing the functionality of our mapping tools to increase the capacity and efficiency of the ML team.
- Documenting workflows, processes, and tools to foster team knowledge sharing.
- Mentoring junior engineers and contributing to team growth through onboarding and collaboration.
Requirements
- Strong background in software engineering with proficiency in Pythonand a track record of building and optimizing high throughput or complex systems at scale.
- Experience in designing, building, and maintaining data processing pipelines, including data preparation and transformation.
- Hands-on experience withmessage queueslikeRabbitMQ, NATS, gRPC, REST or others.
- Familiarity with cloud infrastructure, ops and containerised tools likeK8s, Docker or others.
- Familiarity with modern software development practices, such as automated testing, code reviews, and CI/CD pipelines.
- Analytical and problem-solving skills, with the ability to troubleshoot complex systems and implement effective solutions.
- Professional or personal interest in Research/Machine Learning/Deep-Learning.
- Great communication skills that enable you to collaborate with other Engineering teams.
- Fluency in Englishand the ability to articulate complex technical concepts clearly.
Bonus
- 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.
What we offer
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.
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 and retirement benefits.
Annual L&D budget.
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.
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