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Machine Learning (ML) Engineer - Applied at ModelCat AI. Location Information: Europe. ModelCat  |  Remote from Europe. .  . . About ModelCat. . ModelCat is transforming how companies develop AI models for embedded, edge, and IoT devices. Our innovative platform uses AI to build AI — turning model architecture selection, training, optimization, and validation into a single powerful step.. . ModelCat takes what was previously a 12–24 month process requiring highly skilled AI professionals and reduces it to a 24–48 hour AI-powered job that can be run by developers, data scientists, and product owners. Trusted by industry leaders like NXP and Silicon Labs, ModelCat is a venture-backed startup headquartered in Sunnyvale, California.. .  . . The Role. . We're seeking a motivated ML Engineer to help advance our AutoML platform. You'll play a key role in expanding its capabilities, onboarding new ML use-cases across vision, time-series, and beyond, and improving the product as we scale. This role offers meaningful growth potential toward a technical leadership track.. .  . . What You'll Do. .  . . AutoML Platform Development. . . . Contribute to the development and enhancement of our AutoML system for Edge AI, including pipelines that combine deep-learning and conventional algorithms for embedded devices. . . . Object tracking, multi-model pipelines, and emerging use-cases. . . . . . Build and improve platform features across compute clusters and our web application. . . . Define abstractions and contribute to the architecture of cloud, cluster, and embedded components. . . . ML Use-Case Expansion. . . . Integrate new ML use-cases across a broad range of data domains and maintain and improve existing ones, including:. . . . Time-series and audio, object re-identification, segmentation and keypoints. . . . Action recognition (video), radar and point cloud data, multi-modal (vision + audio + sensor). . . . Small language models (NLP/SLM), classification, and object detection. . . . . . Work with foundational computer vision and non-CV ML models — train, evaluate, modify, and combine them to unlock new functionality. . . . Edge AI Optimization & Deployment. . . . Optimize AI solutions for edge devices using TinyML frameworks, creating models that fit a range of chip sizes and memory constraints. . . . Deploy ML and non-ML algorithms on embedded targets (MCU and application-class microprocessors). . . . Productize research-quality code into robust, production-ready systems. . . . Collaboration & Craft. . . . Partner on data strategies, preprocessing pipelines, and model training workflows. . . . Stay current with Edge AI and AutoML advancements. . . . Document your work and contribute to technical reports. . . .  . . Who You Are. . Required. . . . Master's degree in CS, EE, or a related field (PhD a plus). . . . 4+ years of relevant industry experience in ML (AutoML and Edge AI experience highly valued). . . . Strong Python skills with the ability to write production-quality code; C/C++ a plus. . . . Solid command of ML frameworks: TensorFlow, PyTorch, ONNX. . . . Proficient with the standard DS toolset: scikit-learn, OpenCV, pandas. . . . Comfortable working in Linux-based development environments. . . . Experience onboarding new ML use-cases and expanding into new data domains. . . . Excellent problem-solving skills and strong written and verbal English communication. . . . Preferred. . . . Experience with cloud platforms (AWS) and web technologies (Node.js, REST APIs). . . . Familiarity with compute cluster tools such as Ray and Optuna. . . . Knowledge of model compression techniques: pruning, quantization, transfer learning, knowledge distillation. . . . Experience defining software architecture for ML systems. . . . Familiarity with CI/CD practices. . . . Understanding of embedded systems concepts. . . . Experience with non-ML algorithms and signal processing. . . . Mindset. . . . Proactive, entrepreneurial approach — you thrive with ownership and ambiguity. . . . Startup mentality: you move fast, learn faster, and care deeply about the outcome. . . . Why Join ModelCat. . . . Market Opportunity — Edge AI is exploding, and we're solving a critical pain point in a massive and growing market. . . . Real Customer Impact — Our platform compresses 12–24 months of model development into 24–48 hours — validated by customers like NXP and Silicon Labs. . . . Technical Depth — Work on hard, meaningful problems at the intersection of AutoML, TinyML, and embedded systems. . . . Growth Trajectory — Join during a pivotal growth phase with significant room to grow into technical leadership. . . . Competitive Compensation — Base salary, performance-based bonus, and meaningful equity stake. . . . ModelCat is an equal opportunity employer committed to building a diverse and inclusive team.. .