MOIN,
BERLIN

Training Infrastructure Engineer Salary: €80,000 to €150,000 equity Location: Fully remote within Europe (CET ±2 hours) Stage: Recently funded Series A AI startup We are partnering with a fast-growing generative AI company building the next generation of creative tooling. Their platform generates hyper-realistic sound, speech, and music directly from video, effectively bringing silent content to life. The technology is already being used across gaming, video platforms, and creator ecosystems, with a clear ambition to become foundational infrastructure for audio-visual storytelling. Backed by top-tier venture capital and fresh Series A funding, the company is now scaling its core engineering group. This is a chance to join at a point where the technical challenges are deep, the scope is wide, and individual impact is unmistakable. The Role:As a Training Infrastructure Engineer, you will own and evolve the full model training stack. This is a hands-on, systems-level role focused on making large-scale training fast, reliable, and efficient. You will work close to the hardware and close to the models, shaping how cutting-edge generative systems are trained and iterated. What You Will Do:Design and evaluate optimal training strategies including parallelism approaches and precision trade-offs across different model sizes and workloadsProfile, debug, and optimise GPU workloads at single and multi-GPU level, using low-level tooling to understand real hardware behaviourImprove the entire training pipeline end to end, from data storage and loading through distributed training, checkpointing, and loggingBuild scalable systems for experiment tracking, model and data versioning, and training insightsDesign, deploy, and maintain large-scale training clusters orchestrated with SLURMWhat We Are Looking For:Proven experience optimising training and inference workloads through hands-on implementation, not just theoryDeep understanding of GPU memory hierarchy and compute constraints, including the gap between theoretical and practical performanceStrong intuition for memory-bound vs compute-bound workloads and how to optimise for eachExpertise in efficient attention mechanisms and how their performance characteristics change at scaleNice to Have:Experience writing custom GPU kernels and integrating them into PyTorchBackground working with diffusion or autoregressive modelsFamiliarity with high-performance storage systems such as VAST or large-scale object storageExperience managing SLURM clusters in production environmentsWhy This Role:Join at a pivotal growth stage with fresh funding and strong momentumGenuine ownership and autonomy from day one, with direct influence over technical directionCompetitive salary and equity so you share in the upside you help createWork on technology that is redefining how creators produce and experience contentIf you want to operate at the intersection of deep systems engineering and frontier generative AI, this is one of the strongest opportunities in the European market right now.

Research Engineer – Training Optimisation and Infrastructure Location: Berlin - Remote within Europe (±2 hours CET) Level: Mid to Staff Package: Competitive salary plus equity The Opportunity A Series A generative AI company is hiring a Research Engineer to drive optimisation across training strategy and ML infrastructure. The business builds state-of-the-art audio and music generation models and is backed by a leading generative AI fund. The team includes researchers and engineers from Google Brain, Meta FAIR, Amazon, ETH Zürich, and Max Planck. Role Summary You will focus on optimising end-to-end training pipelines for large generative models. This includes GPU-level performance tuning, distributed systems work, and driving efficiency across data, storage, orchestration, and experimentation systems. Key ResponsibilitiesDevelop and refine training strategies including parallelism approaches and precision choices for varied model scales and compute profilesProfile, debug, and optimise single and multi-GPU workloads using tools such as NsightImprove training pipelines covering data storage, data loading, distributed training, checkpointing, and loggingBuild scalable systems for experiment tracking, model and data versioning, and experiment insightsDesign, deploy, and maintain large-scale training clusters using SLURM Ideal ExperienceStrong hands-on experience optimising training and inference workloadsDeep understanding of GPU memory hierarchy and hardware performance limitsExperience tuning both memory-bound and compute-bound operationsKnowledge of efficient attention algorithms and their performance implications at different scales Nice-to-HaveExperience writing custom GPU kernels and integrating them into PyTorchFamiliarity with diffusion or autoregressive modelsUnderstanding of high-performance storage solutions such as VASTExperience running SLURM clusters at scale Why ApplyWork on frontier audio and music generation modelsInfluence training strategy and infrastructure at scaleJoin a high-calibre research and engineering team

Role: LLM Trace Generation Engineer Location: Heidelberg / Remote Salary: Negotiable  About the Company: This stealth startup is building a next-generation AI infrastructure platform designed to maximize GPU utilization, optimize LLM performance, and reduce operational costs for large-scale AI workloads. Their platform simulates, manages, and continuously adapts AI infrastructure, ensuring that every request - from model input to GPU execution - is handled efficiently. By combining deep knowledge of LLMs with intelligent infrastructure orchestration, the company enables faster, more efficient AI model execution at scale. Mission: The LLM Trace Generation Engineer will focus on optimizing LLM performance by analyzing the full request-to-GPU cycle, helping the platform run models as efficiently as possible. Responsibilities:Analyze end-to-end LLM request and GPU processing flows to identify bottlenecks.Work closely with internal GPU experts to implement optimizations.Develop tools and insights to improve LLM performance across the platform.Contribute to the evolution of the AI infrastructure platform, ensuring it scales efficiently with workloads.Requirements:Deep expertise in LLM models.What They Offer:Opportunity to work on a stealth AI startup tackling cutting-edge infrastructure challenges.Collaborative environment with engineers specializing in both ML and GPU systems.Direct impact on the performance and efficiency of large-scale AI workloads.

AI Project Lead – Berlin (Hybrid)Salary: €70,000–€90,000 + BonusHybrid: 3 days per week in our Berlin office, travel to client site 2-3 times a monthWe are looking for a Client-Facing AI Project Lead to join a fast-growing, highly profitable consultancy at the forefront of applied artificial intelligence. Join a team of 30 friendly nerds who work with corporates, NGOs, Mittelstand companies, and scale-ups to create meaningful AI breakthroughs - from fast-paced MVPs to large-scale transformations.Please Note: This is NOT an engineering role. This is a Project Management and Leadership role focused on client delivery, stakeholder management, and driving exponential value. You will be supported by an expert technical team.What You’ll DoBe obsessed with achieving an actual AI breakthrough with the client and delivering exponential value.Lead fast-paced AI projects from inception to complete integration, ensuring alignment with defined goals and scope.Act as the core point of contact for our clients, driving efficient collaboration across functions and organizational borders.Build trust and maintain strong relationships with stakeholders at all levels (The "charm" factor!).Contribute to a growing, high-impact company and help shape its culture and direction.What We’re Looking ForProject Management Expertise: At least 2 years of experience successfully managing projects from start to finish, with a focus on delivering tangible value (ideally in consulting or a related field).High Processor Speed: Incredibly fast in anticipating, analyzing, and solving problems; able to understand technical basics and use tools effectively.Strong Communication: Excellent verbal and written communication skills; ability to lead workshops and confidently handle numbers.Language Skills: Ability to communicate effectively in German (speaking, writing) is required.Academic Foundation: A technical background (Bachelor’s or Master’s) is highly valued.Soft Skills: Demonstrable ability to deal with ambiguity ("See it. Say it. Sort it!") and build lasting trust.Ideally, You Also BringUnderstanding of and experience in AI projects and Machine Learning.Familiarity with project management methodologies such as Agile.High proficiency in both German and English (C1 level or higher).Willingness to travel to client sites 2–3 times per month across Europe.What We OfferAscension: Opportunity to do the best work of your career with significant autonomy and real impact in a key leadership role.Captivating AI Projects: Engage with high-impact projects that offer ample room for experimentation, continuous learning, and growth.Top-Tier Compensation: We offer top-of-market pay for this AI Project Lead role.Professional Environment: Flexible work environment based on trust, collaboration, and our innovative “No rules rules” philosophy.Supportive Culture: Family-friendly policies, flexible hours, and an active commitment to diversity, inclusion, and Female Empowerment (mentorship and leadership support).

Senior Machine Learning Engineer (m/f/d)Join a mission-driven tech team applying cutting-edge AI to the recycling and waste management sector. They’re developing intelligent systems to optimize material detection, sorting, and process efficiency. Making industrial operations smarter and more sustainable. We're looking for a Senior Machine Learning Engineer with strong experience in Machine Learning to help design and deploy advanced models in production environments.What You’ll DoDevelop and deploy ML solutions for image and time-series data (e.g. object detection, anomaly detection, forecasting)Design scalable algorithms and integrate them into real-world systemsStay on top of the latest AI research and apply new technologies (e.g. Deep Learning, LLMs)Lead code reviews, mentor junior engineers, and promote development best practicesMonitor and continuously optimize models in productionWhat We’re Looking For4+ years of experience in CV (e.g. CNNs, YOLO) and time series (e.g. LSTM, Transformers)Strong Python/C++ skills and experience with ML frameworks (e.g. PyTorch, TensorFlow, OpenCV) and Robotics frameworks (ROS1/ROS2)Experience working with Sensors for real-world applications.Proven record of building and deploying real-world ML applicationsSolid math and data analysis skillsFluent in English and German; strong communication and leadership abilitiesWhat We OfferA key role in shaping AI products in an innovative fieldFlat hierarchies, creative freedom, and an agile environmentA diverse, interdisciplinary team and flexible working optionsModern office space and participation in company success (e.g. VSOP)Salary Budget: €80 - 95k (Dependant on Experience)