Engineering Manager - ML (UK)

What we are building

Mimica’s mission is to accelerate the discovery and deployment of automation with AI.

Our first product, Mapper , learns patterns from employee clicks and keystrokes, identifies key steps, decisions and repetition and generates “blueprints” for automation. At the core of our ML pipeline is a technology translating noisy low-level computer actions into a clean, human-readable representation. Alongside creating process maps for automation, we’ve launched a companion tool, Miner , which helps enterprises identify and prioritize automation opportunities.

Your mission

In this role, you’ll own the strategic direction of the ML team’s projects, ensuring alignment with business and product goals while addressing technical constraints. You’ll actively contribute to the architecture and development of machine learning systems, guiding your team through technical challenges, code reviews, and 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.

Part of your day-to-day

• 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 retrospectives.

• Collaborate with the CTO, Platform and Product to align team priorities with company OKRs.

• Collaborate with the People team on recruiting and onboarding talent that matches our values and technical excellence.

• Facilitate and lead discussions that drive the development and deployment of ML models, optimizing tools and infrastructure for efficiency, while upholding engineering excellence.

• Ensure the delivery of large-scale ML projects by transforming business requirements into actionable solutions and maintaining high standards of quality and performance.

• Identifying and resolving bottleneck and efficiency blockers, enabling the team to iterate faster.

• Championing initiatives to improve the quality, security and performance of our systems and processes, while upholding high standards in our codebase.

• Promoting a culture of collaboration and continuous learning, mentoring team members in their development.

Requirements

• Significant experience in leading and executing machine learning initiatives , particularly in high-growth and large-scale production environments.

• Proven track record in managing and growing cross-functional teams , including hiring, mentoring, and developing ML/AI talent.

• Strong background in applied AI/ML research, development, and deploymen t – particularly in embeddings or transformer models.

• Deep understanding of ML engineering practices, including MLOps, data engineering, and GenAI.

• Expertise in collaborating with Product and Engineering teams to align ML efforts with broader product goals and UX.

• 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.

Bonus

• Familiarity with data pipeline architecture and optimizations.

• Experience working in a distributed systems environment, including familiarity with microservices, load balancing, and scaling.

• Experience with secure software design and data protection mechanisms.

• Background in high impact startup/scale-ups, driving iterative development and rapid delivery.

• Active interest in automation and task-mining

Benefits

We take a structured approach to determining salaries and take into consideration our salary framework, market data, and candidates’ skills. We also offer health benefits and ample paid time off, as well as valuable non-monetary perks such as flexible schedules and location, end-to-end ownership and the opportunity to contribute to projects that are poised to shape the future of work.

#J-18808-Ljbffr