Level: Senior

Job Feld: IT, Data, DevOps

Anstellung: Vollzeit

Vertragsart: Unbefristetes Dienstverhältnis

Gehalt: ab 3.843 € Brutto/Monat

Ort: Linz

Arbeitsmodell: Hybrid, Onsite

Job Zusammenfassung

In dieser Rolle entwickelst du fortschrittliche ML- und DL-Modelle, verwaltest den gesamten ML-Lifecycle und implementierst effektive MLOps-Praktiken zur Sicherstellung der Modellzuverlässigkeit und -skalierbarkeit.

Job Technologien

Deine Rolle im Team

Design and Implement Models: Research, develop, and deploy advanced machine learning and deep learning models for high-impact, real-world applications.
Drive the ML Lifecycle: Own the end-to-end process from initial data exploration and high-quality dataset creation to model training, tuning, validation, and production deployment.
Establish MLOps: Implement robust MLOps practices, including Continuous Integration/Continuous Deployment (CI/CD), automated monitoring, containerization (e.g. With Docker) and infrastructure automation to ensure model reliability and scalability.
Drive Improvement & Learning: Focus on prompt engineering, quantitative output evaluation and data labeling strategies. Create strategies to assure high quality model outputs.
Collaborate and Integrate: Partner closely with Product Managers, Software Engineers, and QA teams to seamlessly integrate AI solutions into our core product ecosystem.

Unsere Erwartungen an dich

Qualifikationen

Foundational Knowledge: Solid theoretical and practical understanding of ML algorithms, deep learning architectures, statistical modeling, and data analysis principles.
Analytical Rigor: Excellent analytical and quantitative problem-solving skills, with a data-driven approach to decision-making and performance validation.
Effective Communication: Ability to clearly articulate complex technical concepts and model limitations to both technical peers (Software Engineers) and non-technical stakeholders (Product Managers and Leadership).
Proactive Collaboration: You are a team player who thrives in a cross-functional environment, actively seeking feedback and driving collaborative solutions for integration challenges.
Ownership Mentality: You take full ownership of your projects, from initial concept through deployment and ongoing monitoring in production.

Erfahrung

Technical Proficiency: Strong expertise in Python and hands-on experience with core AI/ML libraries, specifically PyTorch, TensorFlow, and/or scikit-learn.