Level: Senior

Job Field: IT, Data, DevOps

Employment Type: Full Time

Contract Type: Permanent employment

Salary: from 3.843 € Gross/Month

Location: Linz

Working Model: Hybrid, Onsite

Job Summary

In this role, you will develop advanced ML and DL models, manage the entire ML lifecycle, and implement effective MLOps practices to ensure model reliability and scalability.

Job Technologies

Your role in the 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.

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Our expectations of you

Qualifications

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.

Experience

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

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