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As Engineering 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. You will: - 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 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. - You have a strong background 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 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.

Das wird geboten

Diverse and internationally distributed team: joining our team means becoming part of a large, global community with people of more than 90 nationalities. We re more than just colleagues; we re a group of professionals with a shared mission to connect diverse cultures. Our global presence is growing–we ve doubled in size nearly every year, with our employees based in the UK, Germany, the Netherlands, Poland, the US, and Japan, and we continue to expand our network. - Open communication, regular feedback: as a language-focused company, we value the importance of clear, honest communication.

We value smooth collaboration, direct and actionable feedback, and believe that leading with empathy and growth mindset makes us better together. - Hybrid work, flexible hours: we offer a hybrid work schedule, with team members coming into the office twice a week. This allows you to engage directly with your team and experience the unique energy of our workspace, while still enjoying the flexibility and comfort of working from home. With flexible working hours and trust in your productivity, we are in sync with your team’s general locations and time zones to foster effective and seamless collaboration. - Virtual Shares - An ownership mindset in every role.

We believe everyone should share in our success, and that’s why every employee receives Virtual Shares, linking your contribution directly to DeepL’s growth and rewarding you with a stake in our future. - Regular in-person team events: we bond over vibrant events that are as unique as our team, from local team and business unit gatherings, to new-joiner onboardings, to company-wide events that bring us all together–literally. - Monthly full-day hacking sessions: every month, we have Hack Fridays, where you can spend your time diving into a project you re passionate about and get the opportunity to work with other teams–we value your initiatives, impact, and creativity. - 30 days of annual leave: we value your peace of mind. With 30 days off (excluding public holidays) and access to mental health resources, we make sure you re as strong mentally as you are professionally. - Competitive benefits: just as our team spans the globe, so does our benefits package. We ve crafted it to reflect the diversity of our team and tailored it to align with your unique location, to ensure you feel supported every step of the way.

If this role and our mission resonate with you, but you re hesitant because you don t check all the boxes, don t let that hold you back. At DeepL, it s all about the value you bring and the growth we can foster together. Go ahead, apply—let s discover your potential together.

We can t wait to meet you! #LI-JB1 We are an equal opportunity employer You are welcome at DeepL for who you are - we appreciate authenticity here. Our product is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all succeed, contribute, and think forward!

So bring us your personal experience, your perspectives, and your background. It’s in our diversity that we will find the power to break down language barriers in the world.

Zur Position

Meet DeepL DeepL is a global AI product and research company focused on building secure, intelligent solutions to complex business problems. Over 200,000 business customers and millions of individuals across 228 global markets today trust DeepL s Language AI platform for human-like translation, improved writing and real-time voice translation. Founded in 2017 by CEO Jaroslaw “Jarek” Kutylowski, DeepL now has around 1,000 passionate employees and is supported by world-renowned investors including Benchmark, IVP, and Index Ventures.

Our goal is to become the global leader in trusted, intelligent AI technology, building products that drive better communication, foster connections, and create a meaningful impact. To achieve this, we need talented people like you to join our journey. If you’re ready to shape the future of AI and grow your career in a fast-moving, purpose-driven environment, DeepL is your next destination.

What sets us apart What sets us apart is our blend of cutting-edge AI technology, meaningful work, and a culture where people truly thrive. We’re a team of innovators, researchers, and creators driven by a shared purpose to unlock human potential by making work simpler, smarter, and more connected. When we share what it’s like to work at DeepL, the reactions are overwhelmingly positive.

This might be because of our technology that helps millions of people and businesses communicate and work better every day, or because of the trust, curiosity, and care that shape our culture. What we know for sure is this: being part of DeepL means joining a team dedicated to innovation, growth, and well-being. Discover more about life at DeepL onLinkedIn,Instagram, and our Blog.

Meet the team behind this journey You will lead the Production Inference team — the group responsible for the systems that serve DeepL s language AI models reliably and efficiently at scale. We sit at the intersection of research-grade technical ambition and production-grade operational discipline: our work determines whether DeepL s models reach users with the latency, reliability, and cost profile that makes commercial deployment viable. The team owns the full model serving stack — from GPU-resident inference runtimes and deployment infrastructure through to the developer platform that enables every other research team to bring their models to production.

We operate within the Research organisation, with close ties to DeepL s infrastructure and platform functions, and our architectural decisions affect every product DeepL ships. The broader Research organisation publishes regularly at ACL, NeurIPS, and EMNLP, and the Production Inference team brings that same culture of rigour and innovation to the systems layer of AI.