Senior Machine Learning Engineering Manager
Hybrid (London), Hybrid (Amsterdam), Hybrid (Munich)Full-timePosted 2mo ago
About the role
Senior Engineering Manager leading the Production Inference team, responsible for production-grade model serving systems, reliability, efficiency, and cost-performance of DeepL's language AI model serving stack.
Responsibilities
- Lead and develop a high-performing team of research scientists and ML engineers, building development plans, fostering a candid feedback culture, and maintaining high standards of technical rigour and delivery.
- Own the team's research and development roadmap for production inference systems, balancing near-term reliability with longer-horizon research bets on inference efficiency and architecture.
- Act as the primary technical interface between the Production Inference team and adjacent functions (foundational models research, voice research, applied research, infrastructure, and product).
- Drive the reliability, efficiency, and cost performance of DeepL's model serving stack, including decisions around serving infrastructure evolution (load balancing, autoscaling, runtime selection, hardware utilization).
- Operate with autonomy, defining the team's direction and delivering results amid evolving or ambiguous requirements from product or commercial stakeholders.
- Identify, assess, and recruit research and engineering talent as the team scales.
Qualifications
- Proven experience leading a team of researchers or ML engineers with talent development, delivery rigour, and balance between research quality and production reliability.
- Strong background in Computer Science, Mathematics, Physics, or a comparable quantitative field, or strong ML/systems background with research depth.
- 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 advantageous.
- Comfort working across the full model lifecycle—from training handoff to production deployment, monitoring, and efficiency improvements, with understanding of infrastructure and compute constraints.
- Excellent communication skills with ability to translate complex technical direction into clear goals for technical and non-technical stakeholders.
- Solution-oriented and decisive, able to define direction and drive outcomes without waiting for direction from above.
Skills
Required:Leadership of research/ML teamsProduction ML systemsCross-functional collaboration
Nice to have:LLM inference / inference optimisation
Benefits
- Diverse and internationally distributed team: global presence with 90+ nationalities and locations in the UK, Germany, the Netherlands, Poland, the US, and Japan.
- Open communication and regular feedback culture with emphasis on empathy and growth.
- Hybrid work with office twice a week and flexible hours.
- Virtual Shares granting ownership in the company.
- Regular in-person team events and monthly Hack Fridays.
- 30 days of annual leave (excluding public holidays) with mental health resources.
- Competitive location-tailored benefits package across global locations.
Last updated Oct 22, 2026. Interested? Apply on the company site.
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