Head of Machine Learning; Remote Europe​/Americas

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.

⚠️ Important:
All legitimate communication from Mimica will come from an official email address. While initial outreach may occur via Linked In, all formal hiring communication will take place via email. We do not request banking, financial, or sensitive personal information (such as Social Security Number or ) during the recruiting process.

• 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

You will join us as our Head of Machine Learning, and report to our CTO. You’ll manage a Chapter of 9 Machine Learning Engineers, including 3 Team Leaders. You’ll have a mix of People Management and project coordination responsibilities.

You'll understand the strategic direction of the ML team's projects, with the intention to coordinate projects, dependencies, allocate resources, and ensure strategic alignment with business and product goals.

You'll contribute to the architecture and development of our systems by empowering the team through 1:1s, code reviews, and discussions to facilitate the delivery of impactful features. Your leadership will foster a culture of growth, efficiency, and technical excellence, driving the execution of key ML initiatives that support the company’s broader vision.

• Lead and nurture a growing team of machine learning engineers, supporting their career development through coaching and mentorship.
• Leading team OKR discussions, coordinating projects and facilitating team meetings, planning and retros.
• Collaborate with the CTO, Platform and Product Managers to align team priorities with company OKRs.
• Collaborate with the People team on recruiting and onboarding talent that matches our values and technical excellence.
• Act as a sounding board for the team, empowering the team, and support identifying and resolving bottlenecks and efficiency blockers, enabling the team to iterate faster.
• Drive the development and deployment of ML systems, optimising tools and infrastructure for efficiency, while ensuring timeline and goals are met.
• Promoting a culture of collaboration and continuous learning, and mentoring team members in their development.

• Strong background in applied AI/ML research, development, and deployment
• Significant experience in leading and executing machine learning initiatives, particularly in high-growth and large-scale product companies.
• Proven track record in managing and growing ML/Data Scientist teams, including hiring, mentoring, and developing talent.
• Deep understanding of ML engineering practices, including MLOps and data engineering.
• Expertise in collaborating with Product and Engineering teams to align ML efforts with broader product goals.
• Strong communication skills to engage with senior leaders, product teams, and engineers in complex technical discussions.
• 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 debt.
• Fluency in English, with effective communication skills – articulating complex ideas, concepts, and trade‑offs clearly and getting buy‑in for strategic technical decisions.

• Background in successful startups/scale‑ups,…