deepl - Research Manager | Production Inference

• As Research Manager for the Production Inference team, you will own both people leadership and technical direction for a team of research scientists and ML engineers working on performance-critical model serving systems. While this is not a hands-on coding role, you will be deeply involved in technical reviews, architecture decisions, and research direction for the inference stack. • Lead and develop a high-performing team of research scientists and ML engineers, building strong development plans, fostering a candid and non-retaliatory feedback culture, and maintaining high standards of technical rigour and delivery. • Own the team's research and development roadmap for production inference systems, in close collaboration with senior ICs and cross-functional stakeholders, balancing near-term reliability commitments with longer-horizon research bets on inference efficiency and architecture. • Act as the primary technical interface between the Production Inference team and adjacent functions — including foundational models research, voice research, applied research, infrastructure, and product — ensuring research output is well-scoped, well-communicated, and delivered without creating downstream bottlenecks. • Drive the reliability, efficiency, and cost performance of DeepL's model serving stack, including strategic decisions around serving infrastructure evolution (load balancing, autoscaling, runtime selection, and hardware utilisation). • Operate with a high degree of autonomy, defining the team's direction and pushing for results in an environment where requirements from product or commercial stakeholders can be ambiguous or evolving. • Play an active role in identifying, assessing, and recruiting research and engineering talent as the team continues to develop. • QUALITIES WE LOOK FOR • You hold a PhD (preferable) in Computer Science, Mathematics, Physics, or a comparable quantitative discipline, or possess a strong ML/systems background with equivalent research depth. • You have a strong foundation in production ML systems, inference optimisation, or model serving at scale — direct experience with LLM inference, speculative decoding, quantisation, or serving infrastructure is a meaningful differentiator. • You have proven experience leading a team of researchers or ML engineers, with a track record of developing talent, maintaining delivery rigour, and holding the balance between research quality and production reliability. We are open to earlier-stage managers who bring genuine conviction around people leadership. • You are comfortable operating across the full model lifecycle — from training handoff through to production deployment, monitoring, and efficiency improvement — and understand infrastructure and compute constraints without needing to own them directly. • You have excellent communication skills and the ability to translate complex technical direction into clear goals for both technical and non-technical stakeholders. • You are solution-oriented and decisive, able to define direction and drive outcomes without waiting for direction from above.