Mimica shows enterprises where to streamline, standardize, and automate processes across the entire organization — with zero manual effort, and in as little as two weeks. We answer the most important…
Mimica shows enterprises where to streamline, standardize, and automate processes across the entire organization — with zero manual effort, and in as little as two weeks. We answer the most important…
Core product: AI-powered task mining & process intelligence (Mapper, Miner)
Total disclosed funding: ≈ $27.1M
Recent round: Series B $26.2M (Sep 24, 2025)
Company Overview
Problem Domain
Process discovery, task mining, and automation prioritization for enterprise operations.
Founded
2018
Industry
Software Development
Funding Track Record
Series A- November 2021
$6M
Series B- September 24, 2025
$26.2M
Continued participation from Khosla Ventures, LGVP, and Entrepreneurs First
Investor Signal
“Backed by institutional venture investors including Khosla Ventures and Paladin Capital Group; other named backers include LGVP and Entrepreneurs First.”
Founders
What we do
Join the Team
Head of Machine Learning
RemoteUnited Kingdom, Europe, GB
Remote • United Kingdom, Europe, GB
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Who you are
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, driving iterative development and rapid delivery
Experience working in a distributed systems environment
Experience with general software design and data protection mechanisms
What the job involves
Benefits
Flexible schedules & location
Flexible PTO and sick-leave
Share options
Pension & retirement options
Team socials & off-sites
Book club & learning groups
Startup jobs. A lot of them.
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You will join us as our Head of Machine Learning, and report to our CTO
You’ll manage 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
