Senior Software Engineer | Voice | Full-Stack

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 on LinkedIn , Instagram , and our Blog .

Meet the team behind this journey

DeepL is not just a translation tool. We are building the Operating System for Global Communication. We are the rare AI company that builds the entire stack in house, from training next generation LLMs on our own NVIDIA DGX SuperPODs to delivering real time Language AI to over 300 million users and more than 200,000 businesses globally.

You will join DeepL Voice, the team defining what is possible in real time interpretation. Our translation engine conquered text. Voice is conquering the physical world: fluid, real time conversation for frontline workers, global meetings and enterprise teams.

This is a zero to one engineering environment. We launched our first customer facing features and we are only at the start. The problems are the hard problems of AI interaction. How do you remove the flickering effect of an unstable transcript. How do you chain chunked inference and still hold the latency budget. How do you deliver an audio stream that feels natural rather than robotic. And how do you build any of it when the requirements come out of active research and are still moving.

You will work in a tight cross functional squad alongside researchers, product managers and designers. We are not wrapping an API. We are building the models, the streaming architecture and the interfaces that let people speak without a barrier between them.

Your responsibilities

Own a surface end to end. You will take a part of the Voice product from problem definition through architecture and delivery all the way to operation in production, across the whole path from interface to inference.

Build where the requirement is still moving. You will make progress under genuine ambiguity, working directly with product and research on problems whose shape is still changing. You will know what to build now, what to defer and what not to build at all, and you will be able to explain the difference.

Make the latency and quality calls. The interesting decisions here are trade-offs a metric cannot settle: a mitigation that improves quality and costs delay, a model that is better and slower. You will make the call and own the consequence.

Set the standard and lift the team. You will own technical design for medium to large efforts, define testing and incident standards for a product where failures are immediately audible, lead the hardest debugging, and mentor the engineers around you.

Qualities we look for

A zero to one builder mindset. You do not need a roadmap to build, you need a problem. You are comfortable prototyping a feature in the morning and refactoring it for scale in the afternoon.

Depth in real time systems. Real experience with WebRTC, WebSockets, streaming architectures or latency sensitive systems in production, and a working understanding of where the time actually goes.

Full stack fluency with real range. React and TypeScript on the frontend, C# on the backend, or a language that transfers. You can follow a latency problem across every layer it touches.

High agency. You do not wait for permission. If the transcript is flickering and nobody owns it, you own it. If a research constraint is undocumented, you write it down and take it to the people who can change it.

AI native velocity. You use AI powered tools to accelerate your work and remove repetitive toil. Boilerplate, test generation and debugging go to the tools so your own attention goes to the decisions that matter. You know where the tools are reliable and where they are not, and you check the output rather than trusting it.

A note on our process: We hire into a specific team. This role sits in our Voice team, and the interview process is run by the people you would actually work with, including the hiring manager for this team. That means the conversations are about problems this team genuinely owns rather than generic exercises, and it means we can be honest with you early about whether the fit works in both directions. If we think you are strong but a better match for a different part of engineering, we will say so and introduce you.