Engineering Manager - ML/AI Research

February 10

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Mimica

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Mimica is an AI-powered tool that specializes in process discovery and automation within organizations. It observes teams at work for just one week to generate accurate process maps, uncover inefficiencies, and provide recommendations for automation based on potential time savings. Mimica's technology eliminates the need for manual process discovery by automatically capturing data on employee tasks, allowing businesses to focus on high-return improvement opportunities while ensuring world-class data security and compliance with industry standards.

Machine Learning • Artificial Intelligence • RPA • Process Mapping • Process Discovery

51 - 200 employees

Founded 2018

🤖 Artificial Intelligence

☁️ SaaS

⚡ Productivity

📋 Description

• You'll be the first Engineering Manager of Mimica's Machine Learning Team - and 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. • Lead, nurture and scale a remote team of 8+ machine learning engineers, supporting their career development through 1:1s, coaching, mentorship and performance reviews. • Lead team OKR discussions, coordinating projects and facilitating the Weekly planning and team meetings. • 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 by being a part of interviewing, debriefs, defining scorecards and onboarding plans. • Facilitate and lead discussions that drive the development and deployment of our new generation of ML models, optimizing tools and infrastructure for efficiency, while upholding engineering excellence. • 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, processes and code. • Promoting a culture of collaboration, transparency, feedback and continuous learning.

🎯 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 deployment - particularly in embeddings or transformer models. • Deep understanding of good ML engineering practices, including MLOps, data engineering, and scalability. • 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.

🏖️ Benefits

• 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