As an ML Research Engineer at SEMRON, you will design the algorithms and quantization schemes that unlock efficient, high-accuracy inference
We’re hiring researchers to advance foundation models for structured data, with particular interest in structured data, in-context learning,
Improve our computer vision pipeline end to end, from person and hand tracking to action recognition with VLMs - Fine-tune and evaluate visi
Create & Innovate: Actively participate in the conceptualization phase.
Entwickelt und trainiert Deep-Learning-Modelle für Wahrnehmung und Navigation autonomer Schwermaschinen und integriert sie in Robotiksysteme.
Wir schreiben dir, sobald eine neue geprüfte Stelle dazukommt. Höchstens eine Nachricht am Tag, und nur, wenn es tatsächlich etwas Neues gibt.
Abmelden mit einem Klick, jederzeit. Keine Weitergabe an Dritte.
Tabular data breaks the assumptions that make scaling work for language and vision.
You will have ownership over designing, building, and scaling the core systems that bring Prior Labs foundation models to the world.
We are looking for software engineers with expertise in ML-first perception, prediction or planning for autonomous vehicles or mobile robots.
Collaborate with our core development team to bring machine learning into production - Design and train ML models on large-scale clinical da
At Mirelo, you’ll work at the centre of how we build the next generation of multimodal video-to-audio models.
Optimiert und betreibt die Trainingsinfrastruktur für generative Audiomodelle: GPU-Profiling, verteiltes Training und SLURM-Cluster.
Entwirft und trainiert neuronale Audio-Codecs für generative Sound-, Musik- und Sprachmodelle und prüft deren Nutzen in Downstream-Experimenten.
Design and adapt vision-language and video models for scene understanding, temporal reasoning and activity / action recognition - Build and
You’ll build the autonomy brain for a cutting-edge autonomous aerial platform that will actually take flight.
Intro We are looking for an AI Research Engineer to join the PAIR team and play a central role in the design, development, experimentation,
Entwickelt und trainiert generative 3D-Weltmodelle und Diffusionsmodelle für Bild und Video, inklusive verteiltem Training und Produktivsetzung.
Your mission dida is a machine learning software company with exciting problems for instance in computer vision and natural language processing.
Your mission You will - work on machine learning research projects, in particular addressing the question of how machine learning methodolog
sensmore is a Berlin/Potsdam-based robotics startup delivering production-proven automation for industries where the world’s raw materials a
Entwickelt KI-Systeme, die Vision und Sprache für die Autonomie schwerer Robotermaschinen verbinden, und begleitet sie bis zum Produktiveinsatz.
SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and the simulation of reality.
SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and simulation.
As an AI/ML Engineer, you will play a crucial role in designing, developing, and optimizing machine learning models to power our mobile applications.
As an AI Product Manager at Air Apps, you will be at the forefront of shaping AI-powered applications that enhance user experiences.
Warum dieser Job gelistet ist
Eindeutige KI-Rollenbezeichnung im Stellentitel. Prüfverfahren ansehen
As an ML Research Engineer at SEMRON, you will design the algorithms and quantization schemes that unlock efficient, high-accuracy inference on our analog in-memory compute platform. Your work will bridge cutting-edge quantization research, mathematical modeling, and hardware-aware algorithm design, ensuring that deep neural networks execute with maximal accuracy and throughput on our custom silicon.
: - Research and develop novel analog-aware quantization methods (PTQ and QAT) tailored to in-memory compute constraints - Design mathematically principled matrix-vector multiplication algorithms that exploit sparsity, noise resilience, and non-idealities to improve hardware efficiency - Collaborate with analog hardware engineers to define algorithmic requirements and guide co-development of compute primitives What you should bring in: - PhD or equivalent research experience in machine learning, applied mathematics, or a related field - Strong understanding of quantization, model optimization, and numerical methods for DNNs - Proficiency in Python and PyTorch, with the ability to rapidly prototype and evaluate research ideas - A research mindset: curiosity, rigor, and the ability to explore and discard ideas efficiently Helpful but not required: - Contributions to quantization libraries or novel compression methods - Publications in top-tier ML venues (NeurIPS, ICLR, ICML, etc.) - Familiarity with analog computation challenges (noise, nonlinearity, limited precision, etc.) and the ability to abstract them into robust algorithms - Experience collaborating with hardware teams or formulating algorithm-hardware co-design strategies Why us? We’re building at the intersection of math, hardware, and machine learning, pushing the boundaries of what s possible in compute. If you’ve implemented your own MVM kernels just to see what happens, trained quantized models for fun, or love thinking deeply about efficiency, sparsity, and how to make models run faster and better, you’ll feel right at home. As a small, technical team, early work defines the future of the stack, and we treat it that way. You ll own critical pieces of what we build, with equity to match. No hierarchy, no bureaucracy, just ideas, experiments, and real impact. You’ll grow as fast as you can grow.
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