AILY LABS develops an AI-powered decision intelligence app for businesses. Available on mobile platforms, the app helps teams make faster, better-informed decisions and improve productivity and performance. Registered as Aily Labs GmbH, the company is based in Munich, Germany.
Lead AI/ML Engineer — AILY LABS, Spain (Hybrid)
Lead the development of production AI/ML infrastructure for AILY LABS’ enterprise decision intelligence platform. Manage a team of four or more engineers and guide technical initiatives across Spain, with Madrid or Barcelona named in the role summary.
Сипаттама
- Build and operate machine learning pipelines from data processing through deployment and monitoring.
- Develop APIs, tools, and libraries that support more than 100 AI team members.
- Present findings, identify opportunities, and explain the product and its software and AI foundations.
- Coach junior colleagues on technical work.
- Direct complex projects and technical initiatives from initial design to delivery.
- Maintain the quality of individual contributions and team output.
- Work with DevOps, Front End, Data Engineering, and Back End teams on data exchange and architecture.
- Manage a team of at least four AI/ML engineers and set its roadmap.
- Expand the AI/ML infrastructure and pipelines behind AILY LABS’ decision intelligence platform.
Талаптар
- At least seven years of professional experience.
- Strong grounding in AI and machine learning.
- Proficiency in Python.
- Experience with APIs, Kubernetes, Docker, and cloud platforms.
- Sound software engineering practices.
- In-depth AI/ML expertise.
- Excellent problem-solving ability.
- Willingness and ability to lead and mentor junior colleagues.
- Ability to direct several technical initiatives at once.
- Expertise across the modern AI/ML stack, including AWS, FastAPI, Docker, Kubernetes, Python, CI/CD, Airflow, agentic coding, and concurrency.
- An impact-focused approach and ability to work across AI, business, ML engineering, and product.
- Strong collaboration with data scientists, product managers, and engineers.
- Comfort working through ambiguity with a proactive, hands-on startup approach.