Erzeugt Simulationsdatensätze mit Crash-Solvern, trainiert und evaluiert KI-Physikmodelle für Crashworthiness und validiert sie gegen Ingenieursstandards.
As a Research Scientist at ClickHouse Labs, you will work on high-impact problems at the intersection of database systems, distributed syste
Before the detail, here s the challenge you d help us solve.
Entwickelt und verbessert 3D-Rekonstruktionsmethoden und Szenenrepräsentationen wie Gaussian Splats, von Optimierung pro Szene bis zu Feed-forward-Modellen.
SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and the simulation of reality.
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.
Before the detail, here s the challenge you d help us solve.
The Inference Foundation team owns the core of Mistral s inference stack: the inference engine and its orchestration, from the feature set a
Build and ship models that predict user value, engagement, and reward behaviour.
Leitet die digitale Transformation und Datenanalyse der Arbeitsvorbereitung bei Airbus und automatisiert Prozesse mit RPA, ML und KI.
About Black Forest Labs We’re the team building the foundational layer for visual intelligence: multimodal models trained jointly on images,
The AI Teams at Agile Robots are looking for a Machine Learning Engineer (m/f/d) VLA Training & Evaluation, who will build the frameworks fo
Your Mission At Accenture, you shape the environment in which you thrive – with ways of working that suit you.
Betreut die BioNMR-Anlage, schult Nutzer, baut Python/R-Datenpipelines und integriert ML-Werkzeuge in die Spektrenverarbeitung.
As an Edge AI ML Engineer, you will develop, optimize, and deploy machine learning models for audio and multimodal intelligence on real devices.
Du machst Machine Learning produktionsreif: Du entwickelst skalierbare Daten- und Modell-Pipelines auf AWS und bringst Machine-Learning-Mode
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Aktive Mitarbeit in einem engagiertem BI Competence Center Team Aufbereitung, Analyse, Organisation und Modellierung von Daten Zusammenarbei
Job Title: System Integrator / Software Engineer – Robotic Hand (m/f/d) Location: Berlin, Germany Why this role matters Having secured disru
Baut Signierung, Provenienz und Delta-Updates für KI-Modelle als versionierte Pakete und testet sie auf echter Robotik-Hardware.
Entwickelt Python/Django-Features für eine Praxissoftware und integriert lokal laufende KI-Modelle für Dokumentenklassifikation und Extraktion.
We are looking for a motivated and skilled ML Engineer to join our AI team.
Wir sind ein wachsendes PropTech-Startup aus Münster.
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Airteam is a Berlin-based SaaS startup with an AI-powered cloud platform for roofers and solar planners.
Warum dieser Job gelistet ist
Das Arbeitsergebnis ist ein KI-Modell: Die Rolle umfasst Training und Evaluation von Foundation-Modellen, ohne diese Aufgaben wäre die Stelle nicht mehr vorhanden.. Prüfverfahren ansehen
is to bring deep solid-mechanics expertise into the design, training, evaluation, and deployment of AI Physics Models for real engineering use cases. This is a hands-on technical role. We are looking for someone who understands industrial structural simulation not only conceptually, but through direct experience with simulation models, solver workflows, data generation, validation, and engineering decision-making. You will work with research, product, and customer-facing teams to ensure that our models are useful against real engineering standards — not only benchmark metrics. Relevant application areas may include automotive crashworthiness, aerospace structures, consumer-electronics drop/reliability, manufacturing, durability/fatigue, and other nonlinear structural mechanics problems.
- Work with our research team to define, generate, and iteratively improve simulation datasets for training and evaluating crashworthiness foundation models, balancing coverage of relevant physical scenarios, simulation fidelity, and computational cost. - Design and run high-fidelity simulation campaigns using structural mechanics solvers such as Abaqus, LS-DYNA, Ansys Mechanical, Radioss or equivalent tools. - Define the relevant variation space for training data: geometry, mesh resolution, material behavior, boundary conditions, loading, contact, joints, failure modes, and engineering KPIs. - Build or guide automated pipelines for simulation setup, execution, post-processing, dataset creation, and model evaluation. - Work with research teams to train and evaluate AI models on simulation data, and diagnose failure modes caused by data gaps, poor coverage, numerical artifacts, or model limitations. - Evaluate model outputs against industrial engineering needs, including field-level accuracy, scalar KPIs, deformation modes, load paths, energy absorption, stress/strain fields, failure indicators, uncertainty, and out-of-domain behavior. - Work with industrial customers to understand their simulation workflows and engineering priorities, define use cases and success criteria, and incorporate their feedback into model development and validation. About you - You have deep expertise in crashworthiness, solid mechanics, and structural mechanics, with substantial experience in industrial simulation workflows. - You have a Master’s degree or equivalent technical depth in mechanical engineering, aerospace engineering, civil/structural engineering, computational mechanics, applied physics, or a related field. - You have 4+ years of relevant industrial experience (or PhD +1 years) in domains such as automotive, aerospace, and consumer electronics. - You have hands-on experience with explicit dynamics for crash or impact simulation and understand nonlinear FEM and related topics such as contact, plasticity, structural dynamics, buckling, material modeling, fracture/damage, fatigue, crashworthiness, or durability. - You have direct experience with simulation validation, correlation, model quality, numerical sensitivity, and engineering KPI definition. - You are a strong Python developer who can build and maintain reliable tools for simulation automation, data processing, and model evaluation. You apply sound software engineering practices, including version control with Git, automated testing, code review, and clear documentation. - You have hands-on experience working in Linux and HPC environments, including submitting and monitoring batch jobs, selecting appropriate compute resources, and troubleshooting simulation workflows. You can run simulation campaigns efficiently across a compute cluster. - You are comfortable operating in ambiguous technical environments and turning poorly defined industrial problems into scoped datasets, experiments, metrics, and execution plans. - You communicate clearly with both deep technical experts and non-specialist stakeholders. It would be great if you - Have experience applying machine learning, surrogate modeling, reduced-order modeling, optimization, or data-driven methods to simulation problems. - Have contributed to reusable internal tools, open-source code, simulation automation frameworks, or production-quality engineering workflows. - Have experience working directly with industrial customers, product teams, or engineering decision-makers. - Have publications, patents, internal technical leadership, or recognized contributions in engineering, simulation, computational mechanics, or ML-for-physics communities.
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About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society.
Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.
About the job Mistral AI is looking for a Domain Expert in crashworthiness simulations to help build AI-accelerated simulation capabilities for industrial engineering. You will work at the intersection of industrial simulation, physics modeling, machine learning, and engineering workflows.
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