Senior Research Engineer Machine Learning, AI for Science
Overview The mission of the team is to enable highly accurate and scalable predictions of the electronic structure of molecules and material
Overview The mission of the team is to enable highly accurate and scalable predictions of the electronic structure of molecules and material
Be responsible for a core pillar of Stenon’s products Scale our soil nutrient modelling to support more and more regions across the world Ov
Company team.blue is an ecosystem of 60+ successful brands working together across 22 European countries to provide its 3.3 million SMB cust
Entwickelt und verantwortet die iOS-App, die ein iPhone am Mikroskop mit On-Device-Computer-Vision-Modellen in Echtzeit betreibt.
Definiert die Kamera-Spezifikation für Manipulationsdaten, baut das Bewertungs-Harness und trainiert erste Robotik-Policies auf eigenen Lagerdaten.
Wir schreiben dir, sobald eine neue geprüfte Stelle in Berlin dazukommt. Höchstens eine Nachricht am Tag, und nur, wenn es tatsächlich etwas Neues gibt.
Abmelden mit einem Klick, jederzeit. Keine Weitergabe an Dritte.
At Helsing we deliver AI-based capabilities and the enabling foundation that allow machines to perceive and assist human decision-making.
be part of our Data Science team to further optimize our innovative product based on machine learning and artificial intelligence - work on
Improve our computer vision pipeline end to end, from person and hand tracking to action recognition with VLMs - Fine-tune and evaluate visi
We are seeking a senior machine learning (ML) research developer to join our team working on a novel AI safety agenda.
We are seeking a Senior Machine Learning (ML) Research Scientist to join our team working on a novel AI safety agenda.
Entwickelt und trainiert Deep-Learning-Modelle für Wahrnehmung und Navigation autonomer Schwermaschinen und integriert sie in Robotiksysteme.
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.
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.
Design and adapt vision-language and video models for scene understanding, temporal reasoning and activity / action recognition - Build and
Be part of one of our Data Science teams to further optimize our innovative product based on machine learning and artificial intelligence -
We are seeking a senior distributed machine learning (ML) research developer to join our team working on a novel AI safety agenda.
At Helsing, we are pioneering the future of autonomous decision-making for defence.
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
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.
Your mission Join our ranking team and build the intelligent systems at the core of Cosuno s platform.
Lead R&D efforts to prototype a new robotic manipulator, conducting rigorous testing to validate design specifications and performance criteria.
Warum dieser Job gelistet ist
KI ist Gegenstand der Rolle (Kernbegriffe in Titel/Anforderungen). Prüfverfahren ansehen
Overview The mission of the team is to enable highly accurate and scalable predictions of the electronic structure of molecules and materials using deep learning-powered DFT. Accurate predictions of electronic structure are essential for predictive modeling across chemistry and materials science. Learn more about our work on accurate and scalable DFT in our blog and on our project website.
The primary focus of this role will be developing and maintaining efficient, reliable end-to-end infrastructure for large-scale model training, evaluation, and benchmarking, including large-scale data pipelines for heterogeneous scientific data, distributed training, experimentation, and agentic workflows. If you have solid machine learning engineering expertise and enjoy building scalable infrastructure that enables cutting-edge machine learning research, we encourage you to apply. This post will be open until the positions are filled.
Responsibilities - Develop and maintain efficient, reliable, and scalable infrastructure for large-scale machine learning training, evaluation, and benchmarking. - Architect, design, and implement large-scale data pipelines for heterogeneous scientific data, supporting efficient model training, experimentation, evaluation, and benchmarking. - Build and optimize distributed data processing, model training, evaluation, and benchmarking pipelines. - Develop software and agentic workflows to automate and improve model development, training, evaluation, and benchmarking. - Continuous monitoring and improvement of the stability of data, training, evaluation and benchmarking workflows - Work cross-functionally with machine learning researchers, engineers, and researchers from the natural sciences. - Maintain high standards in code quality and software design. - Document and share practices across the organization. Qualifications Required qualifications: - Completed MSc in computer science, machine learning, AI or a related area - Proficiency in collaborative software engineering in Python - In-depth understanding of machine learning frameworks such as PyTorch and/or Jax - Experience in designing, developing and deploying ML systems - Experience with agentic software development - Experience building and optimizing distributed systems and large-data applications, including those using tensor accelerators or GPUs. - Ability to work in an interdisciplinary collaborative environment, through effective communication of technical concepts to non-experts from different technical backgrounds Qualifications that are considered a plus, but are not strictly required: - PhD degree in computer science, machine learning, AI or a related field, or comparable industry experience in working with machine learning and large datasets. - Experience working with major cloud platforms and/or HPC - Experience developing high-performance scientific software. - Experience designing or developing agentic frameworks, orchestration systems, or infrastructure for building and running AI agents. Software Engineering IC4 - The typical base pay range for this role across United Kingdom is £ 74,700.00 - £ 122,600.00 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: Software Engineering IC4 - The typical base pay range for this role across Germany is € 90,100.00 - € 152,500.00 per year. Certain roles may be eligible for benefits and other compensation.
Find additional benefits and pay information here: Software Engineering IC4 - The typical base pay range for this role across Netherlands is € 78,800.00 - € 133,300.00 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: Software Engineering IC4 - The typical base pay range for this role across United Kingdom is £ 74,700.00 - £ 122,600.00 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer.
All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
Interesse an dieser Position?
Die vollständige Anzeige und das Bewerbungsformular liegen beim Arbeitgeber.
Zur Originalanzeige215 geprüfte Stellen bei 136 Arbeitgebern, 29 davon ortsunabhängig. 86 in der KI-Entwicklung, 70 in Integration & Automatisierung.