• Upgrade ML assets (models, data) management systems for better developer experience and robust governance capabilities • Build and optimize model serving infrastructure with a focus on inference latency and cost optimization • Architect efficient inference pipelines that balance latency, throughput, and cost across various acceleration options • Implement cost-efficient, enterprise-scale solutions • Collaborate in a cross-functional, distributed team for continuous system improvement • Work with MLEs, QA Engineers, and DevOps Engineers • Evaluate and implement new technologies and tools • Contribute to architectural decisions for distributed ML systems

Role Description We are looking for a Senior MLOps specialist. It will be full-time for about 3 months. We are flexible on location and rate for the right person. Mission - Build and run a scalable, traceable, FDA-ready data platform bridging on-prem DGX and AWS for our 2026 submission. Key Responsibilities - Implement ingestion + QC automation starting with CT DICOM, expanding to video/C-Arm and radiology reports. - Implement/operate distributed processing on AWS Batch (Spot) for large-scale QC + predictions + derivatives. - Deploy ClearML for dataset versioning/lineage and experiment tracking (runs/metrics/artifacts; provenance). - Optimize training data access using Lance (or equivalent) for fast loading and incremental updates. - Build a PostgreSQL-backed enrichment service for metadata/labels/predictions independent of raw media (optional search via OpenSearch/text+vector). - Integrate/operate labeling workflows (Encord preferred; alternatives acceptable), incl. RBAC/QC/audit trail + algorithmic label ingestion. - Establish a governed clinical validation environment meeting 21 CFR Part 11 expectations (access control, audit trail/WORM, provenance) and HIPAA/PHI handling. Qualifications - Knowledge of medical imaging (CT, DICOM). - Experience with data ingestion pipelines. - Expertise in data quality (QC) automation. - Familiarity with distributed data processing. - Experience in experiment tracking and dataset versioning. - Knowledge of metadata and label management. - Understanding of clinical AI validation. - Familiarity with 21 CFR Part 11 compliance. - Knowledge of HIPAA/PHI handling. - Experience with RBAC, audit trails, and WORM storage. - Familiarity with vector search and media processing. - Experience in annotation/labeling workflows. - Understanding of provenance and data lineage. - Experience with PACS integration and radiology workflows. Requirements - Proficient in Python. - Experience with AWS (S3, AWS Batch, EC2 Spot). - Familiarity with Kubernetes, HPA, and Karpenter. - Knowledge of Networking (VPC, VPN UiFI). - Experience with Trivy, Jenkins, PostgreSQL, DICOM, PACS, Orthanc, ClearML, Lance, Encord, OpenSearch, and FFmpeg.

Role Description Du brennst für Nachhaltigkeit, Digitalisierung und KI? Dann werde Teil unseres Nachhaltigkeits-Teams und unterstütze unsere Kunden bei der Berechnung ihrer Treibhausgasemissionen, damit sie fundierte, nachhaltige Entscheidungen treffen können. Bei uns bringst du dich im Bereich Kundenbetreuung, Research und Produktentwicklung ein und wirkst damit aktiv an der Weiterentwicklung unserer Services mit, um die Genauigkeit unserer Umweltanalysen zu verbessern und die Kundenzufriedenheit zu steigern. Responsibilities - Du unterstützt bei der Vorbereitung von Kundenterminen zu vielfältigen Fragestellungen im Bereich Bilanzierung von Treibhausgasemissionen. - Du recherchierst zu aktuellen Fragestellungen im Nachhaltigkeitsdiskurs sowie zur entsprechenden Gesetzgebung. - Du entwickelst und optimierst unsere Bilanzierungsmethoden, sodass sie den aktuell geltenden Standards und Richtlinien entsprechen. - Du unterstützt das Team bei der Weiterentwicklung unserer KI, um unsere Tools noch leistungsfähiger zu machen. Qualifications - Du befindest dich im Bachelor- oder Masterstudium in Naturwissenschaften, Nachhaltigkeit, Informatik oder einem verwandten Bereich und hast noch mind. 1 Jahr Studienzeit verbleibend. - Du besitzt erste Erfahrungen in der CO2-Bilanzierung auf Produkt- und Unternehmensebene und verfügst über fundierte Kenntnisse der CO2-Bilanzierungsstandards (z.B. GHG-P, ISO). - Du bringst grundlegende Kenntnisse in Emissionsfaktordatenbanken mit (z.B. ecoInvent, GaBi). - Du verfügst über allgemeine Kenntnisse in relevanten regulatorischen Nachhaltigkeitsvorgaben (CSRD, EU-Taxonomie, CBAM, CSDDD). - Du bringst sehr gute MS Office-Kenntnisse mit, insbesondere im Umgang mit Excel. - Grundkenntnisse in Python für die Datenanalyse und/oder ETL sind von Vorteil. - Sehr gute Englisch- und gute Deutschkenntnisse in Wort und Schrift. - Verfügbarkeit an 2-3 Tagen pro Woche. Benefits - Remote-First-Culture: Du hast die Freiheit von überall in Deutschland aus zu arbeiten. - Offices: Wenn du Lust auf Office Vibes hast, kannst du jederzeit in unserem Büro in Münster vorbeischauen. Darüber hinaus finden Meetings auch in München, Berlin, Düsseldorf und Hamburg statt. - Flexible Arbeitszeiten: Gestalte deinen Arbeitstag nach deinen Bedürfnissen – ohne feste Kernarbeitszeiten, solange es mit deinem Tagesgeschäft & Team vereinbar ist. - Team Days: Unsere Team Days fördern den Austausch abseits des Alltags, ermöglichen neuen Mitarbeitenden das Team kennenzulernen und stärken unsere Unternehmenskultur. - Ausstattung: Du arbeitest mit einem leistungsstarken MacBook, dass dir eine optimale Unterstützung in deiner täglichen Arbeit bietet. - Weiterbildung: Mit unserem Udemy-Pro-Zugang erhältst du uneingeschränkten Zugriff auf Weiterbildungen in deinem Fachbereich und kannst dich so optimal in deinem Bereich weiterentwickeln. - Weitere Benefits: Altersvorsorge von thyssenkrupp, Fahrrad Leasing, Corporate Benefits und viele weitere Extras warten auf dich!

Role Description The role is working within our AI group. The group AI team is a central function that works both with other central groups like marketing and game solutions and the game studios which are part of Tripledot. Within the group AI team, you’ll be working with other AI/ML Engineers, Data engineers, analysts, and product owners. Within the various studios and other central teams, you will interact with data, engineering, and product teams. The role will be directly contributing to main games KPIs such as retention, revenue, player experience, as well as to company efficiency and time to market in developing games and features. Progression opportunities will be within the AI group or to studios in the group. Key Responsibilities - Implement cutting-edge ML algorithms for personalization in gaming, staying abreast of the latest advancements in the field, and testing to see what works best for our games and data. - Design experiments and prototypes to test the viability and efficiency of new AI models. - Translate research findings into real-world applications by creating algorithm prototypes in our codebase. - Convert prototypes into production level code that can be easily managed and deployed through the ML Lifecycle. - Design, develop, and evaluate A/B tests to measure the effectiveness of personalization algorithms and optimise player experience. - Continuously monitor and analyse player data to identify new opportunities for personalization and improve existing algorithms. - Document your work clearly and concisely, fostering knowledge sharing within the team. Qualifications - A Bachelor's degree or higher in a quantitative field (e.g., computer science, mathematics, statistics), another quantitative applied field or equivalent experience. - Strong understanding of industry standard ML techniques (from classification to reinforcement learning and generative methods). - Experience in applying machine learning algorithms to solve real-world problems. - Experience with software development concepts like CI/CD, Version Control, Containers (Docker & Kubernetes) and proven track record of deploying ML models to production and established MLOps concepts. - A good command of analytical programming and visualisation languages and libraries (SQL, python, matplotlib, etc.) as well as some of the supporting tools and platforms (e.g. git, MLFlow, Kubernetes, Kubeflow, Trino, AirFlow). - A strong understanding of statistical concepts (hypothesis testing, sampling, probability distributions). - Excellent communication and collaboration skills to effectively bridge the gap between technical and non-technical teams. - Experience with using generative AI copilots or agents in daily development work. - A passion for mobile gaming and a strong desire to create engaging player experiences and drive business results. Requirements - Bonus points if you also have: - Experience with more complex ML techniques (e.g. Reinforcement Learning). - Experience with A/B testing methodologies in an online gaming context. - Experience working in the games industry. Benefits - Time Off: Statutory Time Off policy for location in addition to bank holidays to relax and refresh throughout the year. - Health & Wellness: Based on country requirements. Private Healthcare or Healthcare stipend subject to eligibility. - Continuous Professional Development: Propel your career with continuous opportunities for professional development.