Computer Vision

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

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)