Development and implementation of integration and verification strategies in line with project planning, with the aim of successfully advancing innovative and intelligent products Definition, further development and continuous optimisation of overarching verification methods based on system requirements and use cases Planning and ensuring all verification activities in terms of schedule, infrastructure, budget and quality standards Coordination, implementation and monitoring of test processes in close cooperation with development departments and verification teams Analysis of test results, risk assessment and derivation of appropriate measures to improve quality Definition of series tests taking into account risk analyses and statistical methods Close cooperation with project managers, development and verification engineers, validation managers and external partners. Completed degree (ETH/university/technical college) in computer science Extensive experience as a test manager and in testing complex, interdisciplinary systems Extensive professional experience in E2E IoT system testing and UI profile testing In-depth knowledge of cloud platforms, device cloud communication, IoT architecture and mobile & apps In-depth knowledge of build, release and DevOps environments as well as test automation.
Python programming experience required Investigate and respond to security alerts in our systems Create and maintain incident response playbooks Keep an eye on current threats and zero-day vulnerabilities in the cyber security space and implement preventative measures within the organization Who you are: min. 5+ years of experience in incident response security You have a background in Cyber Security, Computer Science or IT Operations You are experienced in incident response, blue teaming or digital forensics. Specifically in cloud-native environments You are able to write scripts and programs to automate tasks in Python or another programming language You are proficient with Linux and a SIEM You have experience working with web application firewalls, Cloudflare preferred.
Main Responsibilities: Work directly with Sales Engineers, Product Sales Development Managers, and Sales ManagersAnalyze sales data and pricing trends to support improvements in market‑specific pricingTrack online pricing for vacuum pump technology to assess competitive positioningDesign and generate reports, dashboards, and visualizations for the management teamAttend sales meetings, business functions, service calls, and customer visits alongside account managers and mentorsSupport development of internal data strategies to drive pricing and market‑focused sales initiativesBuild an appreciation for how data influences direct and indirect sales and marketing strategiesPerform other related duties as assignedTo succeed, you will need Skills / Knowledge / Experience: Education level: Must be a Junior or Senior majoring in: Computer ScienceManagement Information SystemsBusiness / Marketing AnalyticsIndustrial Engineering Knowledge areas/Skills: Strong analytical and creative problem‑solving skillsProficiency in Excel and/or Python; Tableau or PowerBI experience preferredSelf‑motivated, independent, flexible, organized, and methodicalResults‑driven, accountable, and ambitiousAdaptability in a dynamic, fast‑paced environmentIn return, we offer We believe there is always a better way.
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.