Your Profile - Qualifications • Bachelor’s/Master’s/PhD in Computer Science, Applied Mathematics, Engineering, or related field. • Strong background in machine learning, deep learning. • Proven experience with 3D graphics, computational geometry (meshes, point clouds, surface reconstruction) or computer vision • Proficiency in Python, C++, and ML frameworks (TensorFlow, PyTorch). • Experience with medical imaging data (CT, CBCT, intraoral scans) is a plus. • Full professional proficiency in English is required Preferred Skills • Familiarity with GANs, diffusion models, or neural rendering for material reconstruction. • Familiarity with biomedical applications. • Strong problem-solving skills and ability to work in interdisciplinary teams. • Excellent communication and documentation abilities. • Large language modules (plus) What We Offer • Opportunity to work on cutting-edge applications in digital dentistry and orthodontics. • Collaborative environment with experts in ML, graphics, and healthcare. • Competitive salary and benefits package. • Career growth in a rapidly evolving field.
As part of our team, you will take on the following responsibilities: You are the driving force that transforms innovative AI/ML concepts from the lab environment into robust, scalable products — ensuring prototypes evolve into stable, production‑ready systems.You operationalize the entire ML lifecycle, developing automated CI/CD pipelines, taking ownership of deploying models into production, and continuously expanding our resilient MLOps infrastructure.You implement algorithms and complex feature transformations efficiently within production systems, optimizing them for latency, throughput, and maximum stability.You build scalable data pipelines and feature stores that ensure reliable, consistent data supply for both training and serving — online and offline.You establish professional monitoring mechanisms such as drift detection, automated retraining, and validation processes to guarantee long‑term model quality in live operations.You collaborate closely with Data Scientists, MLOps teams, and IT Infrastructure teams, ensuring that all production‑grade AI/ML solutions follow software engineering best practices and comply with security, privacy, and regulatory requirements. What makes you stand out You hold a master’s degree in Computer Science, Software Engineering, Mathematics, Statistics, or a related quantitative field.You have at least 3 years of professional experience in ML Engineering or MLOps, with a proven track record of building, deploying, and operating tailored AI/ML solutions in production.You bring deep expertise in Python and SQL, hands‑on experience with cloud platforms (ideally Azure), and familiarity with data warehouses such as Snowflake; foundational knowledge of Infrastructure‑as‑Code tools like Terraform is a plus.You are proficient with CI/CD tools (e.g., Azure DevOps), containerization technologies (Docker/Kubernetes), and apply modern software design patterns confidently.You thrive in a dynamic, agile, and innovative environment, working effectively both independently and as part of a team.You possess excellent English communication skills, both written and spoken; German language skills are considered a plus.
Principal Accountabilities: Collaboration in projects of the European Data Science & Advanced Analytics Team.Concept, design, development and execution of complex innovative AI/Machine Learning solutions as well as execution and implementation of concept studies using advanced statistical methods.Development of deep learning models for structured medical concept extraction from unstructured data.Productionalization of machine learning algorithms in Big Data platforms.Application of modern data mining and machine learning techniques in connection with Healthcare Big Data to identify complex relationships and link heterogeneous data sources.Advanced usage of Large Language Models for summarization, chatbot, entity extraction etc.Develop foundational Deep Learning Models for assets and patients.Builds and trains new production grade algorithms that can learn from complex, high dimensional data to uncover patterns from which machine learning models and applications can be developed. Our Ideal Candidate Will Have: Master’s degree in Computer Science, Mathematics/Statistics, Economics/Econometrics or related field.Substantial years of professional experience in quantitative data analysis or PhD with at least 1 year of relevant professional experience with research in machine learning algorithms.Very good knowledge and in depth understanding of Machine Learning methods, both classical and deep learning models.Relevant experience with Natural Language Processing (NLP) models for extracting structured concepts from unstructured free text, including the design, training, and evaluation of information‑extraction pipelines.Very strong technical capability in Python, SQL, Hadoop ecosystem.Experience applying AI/Machine Learning methods to business questions.Very good knowledge of the higher statistical and econometric methods in theory and practice.Experience with handling Big Data.Ability to write clean, reusable, production-level codeExcellent communication skills (written and oral) including technical aspects of a project, ability to develop usable documentation, results interpretation and business recommendations.Strong analytic mindset and logical thinking capability, strong QC mindset.Knowledge of pharmaceutical market and experience with pharmaceutical data (medical, hospital, pharmacy, claims data) would be a plus, but not a must.Self-responsible for managing projects.Fluency in German & English.
elasticsearch AWS Python Google BigQuery Google Cloud Platform Numpy Pandas Gitlab What you will do Design and develop innovative algorithms to power a personalized shopping experience, leveraging cutting-edge machine learning techniques Deploy your solutions into production, taking full ownership and ensuring high performance and scalability Combine your data science expertise with a pragmatic, agile approach to find innovative solutions and drive measurable results within a fast-paced environment Challenge the status quo by identifying areas for improvement in existing retrieval and reranking systems, particularly those relying heavily on business logic, and propose data-driven solutions Thrive in a dynamic, fast-paced environment with a flat hierarchy, where your ideas and contributions can make a real difference Who you are Proficiency in Python or experience with at least one scientific computing language (e.g., MATLAB, R, Julia, C++) Strong SQL skills with experience in analytical or transactional database environments Theoretical understanding of machine learning principles, coupled with a hands-on approach to building and iterating on models Proven experience in building and deploying machine learning solutions that deliver tangible business value Strong understanding of data structures, algorithms, and tools for efficiently handling large datasets (e.g. pandas, numpy, dask, arrow, polars, …) Experience designing, building, and managing data pipelines Familiarity with cloud-based model training and serving platforms (e.g., GCP Vertex AI, Amazon SageMaker) Solid understanding of statistical methods for model evaluation Big Data: Experience analyzing large datasets using statistical and machine learning techniques DevOps: Familiarity with CI/CD tools (e.g., GitLab CI/CD, Hashicorp Terraform) is a plus Generative AI: Experience with generative AI and agentic frameworks (e.g., LangChain, ADK, CrewAI, Pydantic AI, …) is a plus Understanding of recommendation, retrieval and reranking systems in e-commerce and retail is a plus Excellent written and verbal communication skills in English Ability to effectively communicate complex machine learning concepts to both technical and non-technical stakeholders Proven ability to collaborate effectively within a team to establish standards and best practices for deploying machine learning models A proactive approach to knowledge sharing and fostering a quick development environment Nice to have Experience with BigQuery Knowledge of time series and (graph) neural network models Familiarity with statistical testing and Gaussian Processes Strong Knowledge of Computer Vision libraries, (e.g. OpenCV, TensorFlow, PyTorch) Experience maintaining Machine Learning pipelines through MLOps frameworks (e.g.
Erfahrung mit Self-Supervised Learning (SSL), Transformern oder modernen Architekturen wie Masked Autoencoders (MAE) / JEPA ist ausdrücklich erwünscht. * Methodisches Wissen: Starkes Verständnis von Computer Vision, Representation Learning und hochdimensionaler Geometrie. * Soft Skills: Leidenschaft für die Lösung medizinischer Herausforderungen und die Fähigkeit zur Arbeit in multidisziplinären Teams (Ingenieure, Kliniker).
Erfahrung mit Self-Supervised Learning (SSL), Transformern oder modernen Architekturen wie Masked Autoencoders (MAE) / JEPA ist ausdrücklich erwünscht. * Methodisches Wissen: Starkes Verständnis von Computer Vision, Representation Learning und hochdimensionaler Geometrie. * Soft Skills: Leidenschaft für die Lösung medizinischer Herausforderungen und die Fähigkeit zur Arbeit in multidisziplinären Teams (Ingenieure, Kliniker).
Ihr Profil Du studierst an einer Hoch- oder Fachhochschule und hast Interesse oder idealerweise bereits Vorkenntnisse in einem der folgenden Bereiche: Computer Vision / Bildverarbeitung Deep Learning / Machine Learning Programmierung und Softwareentwicklung (z. B. Python, PyTorch, TensorFlow) Datenanalyse und -aufbereitung Werkstofftechnik oder Beschichtungstechnik Du zeigst: Flexibilität und arbeitest zuverlässig und eigenständig nach Anweisungen Interesse an der Entwicklung von KI-basierten Analysemethoden und deren Integration in Softwarelösungen Pflichtbewusstsein, insbesondere bei der Durchführung wissenschaftlicher Arbeiten Grundkenntnisse im Bereich Werkstoffe und/oder Produktionstechnik sind von Vorteil Gute Sprachkenntnisse in Deutsch und Englisch Ihre Aufgaben Die folgenden Aufgaben bilden den Schwerpunkt deiner Tätigkeit: Einarbeitung in die automatisierte Analyse von Schliffbildern thermischer Spritzschichten Vorbereitung, Aufbereitung und Annotation von Bilddaten für das Training von Deep-Learning-Modellen Unterstützung bei der Implementierung, Training und Bewertung verschiedener Segmentierungsmodelle (z.
Disposition, Faktura, Vertrieb) kennen und arbeitest aktiv mit Somit schließt Du Deine branchenbezogene Ausbildung als hoch qualifizierter Mitarbeiter durch die Verbindung von Theorie und Praxis ab Deine Qualifikationen auf einen Blick Deinen Realschulabschluss hast Du in der Tasche und bist bereit für neue Herausforderungen Darüber hinaus hast Du Interesse an wirtschaftlichen Themen, kaufmännischen Abläufen und möchtest nun die Praxis kennenlernen Der Umgang mit Computern sowie EDV-Programmen fällt Dir leicht und da macht Dir niemand etwas vor Du hast eine kommunikative, offene und teamfähige Persönlichkeit mit einem hohen Maß an Verlässlichkeit, Motivation sowie Lernbereitschaft Eine engagierte und selbstständige Arbeitsweise verbunden mit Kreativität runden Dein Profil ab Unser Angebot für Deinen Einsatz Steige bei uns ein und profitiere von den Stärken, die REMONDIS als Unternehmensgruppe mit sich bringt.
Ihr Profil Du studierst an einer Hoch- oder Fachhochschule und hast Interesse oder idealerweise bereits Vorkenntnisse in einem der folgenden Bereiche: Computer Vision / Bildverarbeitung Deep Learning / Machine Learning Programmierung und Softwareentwicklung (z. B. Python, PyTorch, TensorFlow) Datenanalyse und -aufbereitung Werkstofftechnik oder Beschichtungstechnik Du zeigst: Flexibilität und arbeitest zuverlässig und eigenständig nach Anweisungen Interesse an der Entwicklung von KI-basierten Analysemethoden und deren Integration in Softwarelösungen Pflichtbewusstsein, insbesondere bei der Durchführung wissenschaftlicher Arbeiten Grundkenntnisse im Bereich Werkstoffe und/oder Produktionstechnik sind von Vorteil Gute Sprachkenntnisse in Deutsch und Englisch Ihre Aufgaben Die folgenden Aufgaben bilden den Schwerpunkt deiner Tätigkeit: Einarbeitung in die automatisierte Analyse von Schliffbildern thermischer Spritzschichten Vorbereitung, Aufbereitung und Annotation von Bilddaten für das Training von Deep-Learning-Modellen Unterstützung bei der Implementierung, Training und Bewertung verschiedener Segmentierungsmodelle (z.
Maintain and troubleshoot data integration pipelines to ensure stable data flow into AI and analytics systems Support model development by assisting with training, validation, and optimization of machine learning workflows Conduct data analysis to extract insights and provide clear reports supporting R&D research questions Solve technical challenges related to data access, pipeline performance, and software limitations Ensure continuity of ongoing projects by aligning closely with the core team and delivering on timelines Perform image analysis and prepare datasets required for scientific and ML use cases Manage and improve ETL processes to ensure data quality, structure, and availability Document workflows, pipeline changes, and analytical steps to ensure clarity and reproducibility Academic background in computer science, data science, engineering, or a related quantitative field Strong proficiency in Python with expertise in scientific and analytical libraries Skilled in SQL and working with relational databases Understanding of ETL concepts and practical experience working with data pipelines Solid foundation in machine learning principles and model lifecycle Ability to perform image analysis for scientific or research applications Strong communication and interpersonal skills with the ability to collaborate in a technical team Independent, structured problem-solver with a commitment to clear documentation and FAIR data practices Opportunity to contribute directly to active R&D projects with immediate real-world impact Hands-on involvement in AI, machine learning, and data integration challenges in a scientific environment Close collaboration with a small, highly skilled technical team Ihr Kontakt Referenznummer 863771/1 Kontakt aufnehmen Telefon:+41 44 225 50 00 E-Mail: positionen@hays.ch Anstellungsart Freiberuflich für ein Projekt
Maintain and troubleshoot data integration pipelines to ensure stable data flow into AI and analytics systemsSupport model development by assisting with training, validation, and optimization of machine learning workflowsConduct data analysis to extract insights and provide clear reports supporting R&D research questionsSolve technical challenges related to data access, pipeline performance, and software limitationsEnsure continuity of ongoing projects by aligning closely with the core team and delivering on timelinesPerform image analysis and prepare datasets required for scientific and ML use casesManage and improve ETL processes to ensure data quality, structure, and availabilityDocument workflows, pipeline changes, and analytical steps to ensure clarity and reproducibility Academic background in computer science, data science, engineering, or a related quantitative fieldStrong proficiency in Python with expertise in scientific and analytical librariesSkilled in SQL and working with relational databasesUnderstanding of ETL concepts and practical experience working with data pipelinesSolid foundation in machine learning principles and model lifecycleAbility to perform image analysis for scientific or research applicationsStrong communication and interpersonal skills with the ability to collaborate in a technical teamIndependent, structured problem-solver with a commitment to clear documentation and FAIR data practices Opportunity to contribute directly to active R&D projects with immediate real-world impactHands-on involvement in AI, machine learning, and data integration challenges in a scientific environmentClose collaboration with a small, highly skilled technical team Ihr Kontakt Referenznummer 863771/1 Kontakt aufnehmen Telefon:+41 44 225 50 00 E-Mail: positionen@hays.ch Anstellungsart Freiberuflich für ein Projekt