MOIN,
BERLIN

Engineering Manager Stockholm, Sweden73,000–93,000 SEK per month benefits Hybrid – 3 days office / 2 days remote Full-time Most ML leadership jobs pull you away from the models. This one puts you in charge of them. You will lead the generative audio systems that create music and sound effects for a global content platform used by millions of creators. The models already exist. The research direction is clear. What is needed now is someone who can own the entire system and push it into production at scale. You will guide how large diffusion models for music are trained, evaluated and deployed. Your decisions determine how these models evolve technically and how they run in real products where latency, stability and cost matter. What you will build You will help build systems that automatically adapt music to video, generate sound effects directly from visual input, and allow creators to produce soundtracks in seconds. A small team of five PhD educated ML engineers and a contractor will rely on your technical direction while you shape how the technology moves from experimentation into production. You will work across the full machine learning lifecycle. Training large generative models. Defining evaluation strategies. Making architectural decisions about inference, optimisation and deployment. Working closely with platform and MLOps engineers to ensure the systems run reliably in production.  Why this environment is different The models are trained on a proprietary catalogue of licensed music and structured datasets created through a global network of artists who produce and remix tracks specifically for training. This produces a dataset most AI labs simply do not have. You will also work close to the research frontier, with collaborations involving groups connected to unicorn start up labs and tier 1 universities.  The result is rare: frontier generative model work inside a stable, profitable company where the technology actually ships to users.  What you bringDeep experience training large machine learning models. Experience with generative models such as diffusion, audio models, vision models or large language models. Strong ML system design skills across training, evaluation and production deployment. Comfort guiding engineers and making architectural decisions that shape how ML systems evolve. Experience shipping ML systems where latency, reliability and cost matter. Team and setup You will lead a team of five PhD educated engineers and one contractor working on generative audio systems. The team works closely with platform engineering, data infrastructure and MLOps to ensure models move from experimentation into production features.  Curious? If you have trained large generative models before and want ownership of the entire system rather than a narrow piece of it, this will likely be interesting. Send a message / apply, and I can share more context.

Senior Research Engineer – Generative AIGermany - Remote first €80,000 – €100,000 2 year contract  This role sits inside a research-driven engineering team building real Generative AI systems that are meant to leave the lab and prove their value in the world.It is about building working GenAI agents, putting them in front of partners, stress testing them, improving them and demonstrating that they solve meaningful problems. The domains range from public safety and social services to finance. The common thread is impact. In the first six months, you would join an applied project where the goal is to prototype a GenAI agent and convince an external partner that it creates tangible value. You would work closely with a senior researcher, iterating quickly, shipping regular merge requests, refining features, spotting technical risks early and improving the system week by week. There is a strong emphasis on being able to explain what you built, both to technical peers and to non-technical stakeholders. The environment is intentionally exploratory. New models, new agent frameworks, new tooling. If something promising appears, you are encouraged to test it. The team meets in person every Tuesday in Heidelberg, but beyond that there is flexibility. English is the working language.You might be refining prompts and evaluation loops for LLM-based systems, experimenting with coding agents, shaping system architectures, or mapping out a lightweight roadmap for how a prototype could evolve into something commercial. You will be close to decision making, not buried in a narrow implementation silo.Who we're looking for:Working with LLMs or GenAI in practice since at least 2023, comfortable building in Python with proper version control.A Master’s or PhD in Computer Science, AI or a related field fits well.Industry experience matters more than labels.Experience with coding agents such as Cursor or Codex is particularly interesting, as is familiarity with modern GenAI libraries and lightweight MLOps tooling.Just as important is adaptability. The technology moves fast and so does the direction of applied projects. The interview process is technical but practical. There is an initial technical conversation focused on engineering and GenAI fundamentals, followed by a motivational discussion, and then an in-person day that includes collaborative coding using AI coding agents. The coding session focuses more on how you think and structure a solution than on perfect syntax. This is suited to someone who enjoys building at the edge of what is currently possible with Generative AI, but who also cares whether the result genuinely improves something for real users.If this sounds interesting, please apply here and a member of the team will be in touch.

Senior ML Engineer – Autonomous Driving (Mapless, AI-First) A well-funded European deep-tech company is building fully AI-driven, mapless autonomous driving technology in collaboration with leading OEMs and Tier 1 suppliers. We are hiring experienced ML engineers who want to move beyond incremental ADAS and work on large-scale, AI-native autonomy systems deployed directly on vehicles. What You’ll Work OnLearning-based scene understanding from raw multimodal sensor dataOnline road topology & lane connectivity extractionMultimodal transformers / graph neural networks for dynamic traffic modelingEnd-to-end perception → prediction → planning architecturesEnsuring geometric & temporal consistency in real-world drivingDeployment of production-grade ML models to embedded vehicle systemsThis is not simulation-only research. Models are trained at scale and validated directly on real vehicles. What We’re Looking ForStrong ML fundamentals (deep learning, transformers, large-scale training)Solid Python skills; C for production integrationExperience in one or more of:Autonomous drivingRobotics3D computer visionMultimodal learningSensor fusionLearning-based planningPhD is welcome but not required. Real-world deployment experience is highly valued. Why Join?Flat technical structure with real ownershipStrong compute infrastructureClose collaboration with major automotive partnersEquity / stock optionsOpportunity to shape next-generation autonomy from the ground upLocation: Germany (hybrid model available)

About the Company We’re supporting a venture-backed AI company building cutting-edge surgical AI systems focused on video understanding. Their initial product transforms surgical videos into structured clinical reports - a focused entry point into a much bigger vision: developing a large-scale surgical foundation model, ultimately enabling advanced perception systems and autonomous surgical robotics.This is a deep-tech team building models from first principles - not treating AI as a black box. They combine ambitious research goals with real-world deployment in high-stakes medical environments. The Role Our client is hiring a Computer Vision Engineer who operates at the intersection of research and production. This is not a pure research role - and not just product engineering. They’re looking for someone who can:Deliver research-grade innovationWrite clean, scalable, production-ready codeMove fluidly between experimentation and deploymentYou will work on state-of-the-art video understanding systems that convert unstructured surgical footage into structured intelligence. This role is central to their long-term roadmap toward advanced autonomy. What You’ll Work OnDesigning and training advanced video understanding modelsExtending image-based CV architectures into temporal domainsWorking with multimodal and potentially 3D data (point clouds beneficial)Building scalable training pipelines, including distributed trainingBridging research prototypes into production systemsContributing to publications at leading AI conferencesCollaborating closely with a highly technical founding teamWhat They’re Looking For Technical BackgroundStrong foundation in Computer Vision on imagesExperience in video understandingExposure to 3D data / point clouds (beneficial)Experience with model training pipelines and optimizationAbility to implement research papers quickly and robustlyStrong software engineering fundamentalsResearch MindsetTrack record (or clear potential) for top conference-level workAbility to derive models from first principlesDeep understanding of modern CV architecturesProblem-SolvingComfortable working in ambiguous environmentsStrong analytical and structured thinking skillsAble to tackle unfamiliar domains effectivelyCollaboration & Product AwarenessUnderstands real-world constraints and client needsComfortable working closely with cross-functional teamsThrives in a collaborative environment (not a solo contributor role_Why Consider This Opportunity?Meaningful Impact - Building AI systems that support safer surgical procedures and improve access to care. Big Technical Vision - Report generation is the entry point. The broader roadmap includes foundational models and advanced autonomy systems. Genuine Deep Tech - This team is building core models and infrastructure from the ground up. Publication & Credibility - Publishing at leading conferences is part of the company’s DNA. Strong Talent Density - You’ll work alongside highly technical peers in an ambitious, research-driven environment.

MLOps Engineer Barcelona or San Sebastián, Hybrid Fixed-term contract until 30 June 2026€45,000-€55,000 Salary €3,000 sign-on bonus €500 per month retention bonus €2,000 relocation support EU work authorisation required Total bonus package available over the contract: up to €5,000 depending on start date. You join one of Europe’s most recognised deep-tech scale-ups. Backed by major global investors and strong EU support, they have built one of the most credible AI compression products in the market. This compression tool is already live with major enterprise clients. Now they need more engineers to help deploy, monitor and scale it properly.Why apply? You will work alongside highly technical quantum and AI engineers operating at a very high level. You will gain hands-on exposure to large-scale LLM deployment, distributed training and real-world cost optimisation. You will have a globally recognised deep-tech brand on your CV, working on AI efficiency at scale. That combination of compression, distributed systems and enterprise deployment opens doors across AI infrastructure, LLMOps and high-performance ML environments. You get flexible working hours. Start early, start late, structure your day how you want. Hybrid setup in Barcelona or San Sebastián. You get meaningful bonuses on top of base salary. What you’ll actually be doing Helping take compressed LLMs and get them deployed, monitored and running reliably for enterprise customers. Improving automation, reliability and cost efficiency across the ML lifecycle. Working closely with researchers and platform engineers to bridge research and production.What you'll needExperience running LLMs in production. Comfort working with the infrastructure around them, cloud, containers, CI/CD, Kubernetes, that sort of thing. Someone who understands what it takes to keep ML systems stable, monitored and efficient once they’re live. If you’ve touched production LLM systems and the infra that supports them, this is likely relevant.