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Posted Mar 27Head of Machine Learning (Remote - UK/Europe/Americas)
at Mimica
United KingdomRemote
Responsibilities
- - 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.
- - Drive the development and deployment of ML systems, optimising tools and infrastructure for efficiency, while ensuring timeline and goals are met.
Requirements
- Our AI-powered task mining observes employee actions across the desktop and categorizes them into detailed process maps.
- We have 8 cross-functional teams, including a dedicated Platform team focused on infra & developer experience.
- We started building proprietary ML before the LLM boom, so we don't just consume models - we train them from the ground up.
- 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 YOUR MISSION You will join us as our Head of Machine Learning, and report to our CTO.
- You’ll manage a Chapter of 10 Machine Learning Engineers, including 3 Team Leaders and expand the team.
- 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.
- PART OF YOUR DAY-TO-DAY - Lead and nurture a growing team of machine learning engineers, supporting their career development through coaching and mentorship.
- REQUIREMENTS - 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 Engineers/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.