Werkstudent Prototyping - smart labeling (m/w/d)

📍 Job Overview

Job Title: Werkstudent Prototyping - Smart Labeling (m/f/d)

Company: isento GmbH

Location: Nuremberg, Bavaria, Germany

Job Type: Internship

Category: Software Engineering / Machine Learning Operations

Date Posted: 2026-08-26

Experience Level: Entry Level (0-2 years)

Remote Status: Hybrid

🚀 Role Summary

• This internship focuses on hands-on prototype development and the creation of demonstrators for smart labeling solutions, integrating AI for object detection.

• The role involves working with both backend systems and user interfaces, with a strong emphasis on data pipelines and machine learning model training.

• Successful candidates will contribute to establishing AI and machine learning as integral components of modern software development projects.

• This position offers a unique opportunity to gain practical experience in cutting-edge AI/ML technologies within a collaborative team environment.

📝 Enhancement Note: The "Werkstudent" title in German typically refers to a student working part-time alongside their studies, often implying a focus on practical application of academic knowledge. This role is positioned within Software Engineering with a strong specialization in Machine Learning Operations (MLOps) and AI development, particularly in the domain of smart labeling and object detection.

📈 Primary Responsibilities

• Independently develop prototypes and build functional demonstrators for smart labeling applications.

• Design and implement user interfaces (Web UI) and backend systems for the developed prototypes.

• Integrate and fine-tune AI models, specifically for object detection tasks, using frameworks like PyTorch.

• Connect and manage data pipelines, including data extraction, transformation, and loading from sources like BigQuery and Google Cloud Storage (GCS).

• Develop and deploy REST APIs to facilitate communication between backend services and frontend applications.

• Perform image processing tasks as required for AI model training and evaluation.

• Contribute to the MLOps lifecycle, including experiment tracking and model deployment.

📝 Enhancement Note: While the original description is brief, the responsibilities are inferred from the required skills and the nature of a prototyping role in AI/ML. This involves translating technical requirements into functional prototypes, managing data flow, and ensuring model performance.

🎓 Skills & Qualifications

Education: Currently pursuing a degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, or a related technical field. A strong academic record in relevant coursework is expected.

Experience: 0-2 years of experience, preferably gained through academic projects, internships, or personal projects in software development and machine learning.

Required Skills:

• Python 3.10+: Proficient in writing clean, maintainable Python code for both new projects and understanding existing codebases.

• PyTorch: Practical experience with PyTorch, including custom training loops and model training/fine-tuning.

• Data Pipelines: Experience with cloud-based data platforms such as BigQuery (Google Cloud) and Google Cloud Storage (GCS), including data extraction and transformation processes.

• REST API Development: Ability to design, build, and consume RESTful APIs.

• Web UI Development: Familiarity with developing user interfaces, ideally with modern web technologies.

• Image Processing: Fundamental knowledge and practical skills in image manipulation and analysis.

Preferred Skills:

• ML/AI Project Experience: Prior experience in machine learning or AI projects, particularly in object detection (e.g., using models like Grounding-DINO).

• Data Labeling Formats: Familiarity with common data labeling formats like COCO and pycocotools, including bidirectional conversion and YAML dataset configurations.

• MLOps: Understanding of MLOps principles, especially experiment tracking tools.

• Cross-Platform Deployment: Experience deploying applications across different platforms (e.g., from Windows development environments to Linux GPU servers).

• German Language Skills: Good command of German (minimum B2 level) for effective communication with clients and the team.

📝 Enhancement Note: The "Werkstudent" designation suggests that the candidate is currently enrolled in a university program. The required skills are highly specific to AI/ML development and data engineering, indicating a role that bridges academic learning with practical, project-based work.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Prototyping Examples: Showcase functional prototypes developed for academic or personal projects, demonstrating the ability to translate concepts into working solutions.

• AI/ML Project Demonstrations: Include case studies of AI or ML projects, highlighting the problem statement, methodology, model architecture, and achieved results (e.g., accuracy metrics for object detection).

• Data Pipeline Implementation: Provide examples of data pipelines built for data extraction, transformation, and loading, showcasing proficiency with tools like BigQuery and GCS.

• API Integration: Demonstrate experience with developing or integrating REST APIs in previous projects.

• Code Repository: A link to a GitHub or similar repository showcasing well-documented Python code and project structures.

Process Documentation:

• Workflow Design: Ability to document the design and flow of prototypes and data pipelines.

• Implementation Methods: Clear articulation of the technical steps and tools used during implementation.

• Performance Analysis: Documentation of how model performance and system efficiency were measured and improved.

📝 Enhancement Note: For an internship role, the portfolio emphasis will be on demonstrating potential and foundational understanding rather than extensive production experience. The focus is on showing practical application of learned skills in Python, PyTorch, and data handling.

💵 Compensation & Benefits

Salary Range: As this is a "Werkstudent" position (part-time student employment in Germany), the salary will be commensurate with industry standards for student roles in Nuremberg, Germany, typically ranging from €12-€18 per hour, depending on experience and academic progress.

Benefits:

• Flexible Working Hours: Ability to adjust work schedule to accommodate academic commitments.

• Hybrid Work Model: Combination of remote work and on-site presence, offering a balanced work environment.

• Team Events: Participation in company-organized events such as BBQs, game nights, Duke Days, and summer parties, fostering team cohesion.

• Individualized Growth: Opportunities for personal and professional development through tailored training programs and continuous learning initiatives.

• Excellent Work Culture: A friendly and respectful work atmosphere, recognized by multiple Top Employer awards.

• Exposure to Advanced Projects: Involvement in exciting client projects and internal initiatives in robotics, AI, and Machine Learning.

Working Hours: Typically around 15-20 hours per week, to be agreed upon based on academic schedule and project needs. Full-time during semester breaks may be possible.

📝 Enhancement Note: The salary estimate is based on typical "Werkstudent" compensation in Germany for technical roles, considering the location (Nuremberg) and the entry-level nature of the position. Benefits are directly extracted from the provided text and highlighted for their relevance to student employees.

🎯 Team & Company Context

🏢 Company Culture

Industry: Information Technology (IT) Services and Consulting, with a specialization in custom software development, secure software development, robotics, AI, and Machine Learning.

Company Size: The company description implies a growing, collaborative team environment rather than a large, bureaucratic structure. Based on typical "GmbH" sizes and the emphasis on team cohesion, it's likely between 50-250 employees.

Founded: The company has been operational for at least five years, as evidenced by the "five years in a row awarded as Top Employer" statement.

Team Structure:

• The operations/engineering team is likely structured around project-based work, with small, agile teams collaborating closely.

• Reporting structure is expected to be relatively flat, with direct access to project leads or senior engineers.

• Cross-functional collaboration is a key aspect, involving close work between developers, AI specialists, and potentially project managers or client representatives. Methodology:

• Agile Development: Likely employs agile methodologies for project management and software development.

• Data-Driven Approaches: Emphasizes the use of data for decision-making, particularly in AI/ML model development and optimization.

• Continuous Improvement: Focus on iterative development and incorporating feedback for process and product enhancement.

Company Website: http://isento.de

📝 Enhancement Note: The company culture is described as "team-oriented" and "supportive," with a focus on client satisfaction and delivering high-quality solutions. The "Werkstudent" role is positioned within this culture as an integrated team member.

📈 Career & Growth Analysis

Operations Career Level: This is an entry-level internship ("Werkstudent") role, designed for students to gain practical experience in software engineering and AI/ML prototyping. It serves as a foundational step for a career in these fields.

Reporting Structure: The intern will likely report to a senior engineer or project lead who will provide guidance and mentorship.

Operations Impact: While an intern's direct impact might be focused on specific prototype features or data pipeline components, their work contributes to the development of client solutions and internal AI/ML initiatives, demonstrating the potential for future impact.

Growth Opportunities:

• Skill Development: Gain hands-on experience with Python, PyTorch, AI/ML concepts, data pipelines, and REST APIs.

• Industry Exposure: Work on real-world client projects and internal R&D in robotics and AI.

• Mentorship: Receive guidance from experienced software engineers and AI specialists.

• Potential for Future Employment: Strong performance can lead to opportunities for further internships or full-time positions upon graduation.

📝 Enhancement Note: The growth opportunities are framed around practical skill acquisition and exposure to advanced technologies, which is typical for an internship role in a specialized technical field.

🌐 Work Environment

Office Type: Hybrid work environment, combining on-site collaboration with remote flexibility. The company emphasizes a friendly and respectful atmosphere.

Office Location(s): Primarily based in Nuremberg, Bavaria, Germany, with potential for remote work days.

Workspace Context:

• Collaborative Space: The office likely offers spaces conducive to teamwork and knowledge sharing.

• Technology Access: Access to necessary development tools, potentially including GPU servers for ML tasks.

• Team Interaction: Opportunities for regular interaction with team members and mentors.

Work Schedule: Flexible working hours are offered, with approximately 15-20 hours per week, allowing students to balance their studies with work responsibilities.

📝 Enhancement Note: The hybrid model and flexible hours are key benefits for students, allowing them to integrate work experience with their academic pursuits.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Review of application materials, including CV and cover letter, focusing on relevant skills and academic background.

• Technical Interview: Likely includes a discussion of Python, PyTorch, and AI/ML concepts. May involve a coding challenge or a review of a personal project.

• Portfolio Review: Discussion of the candidate's portfolio, focusing on demonstrated skills in prototyping, AI/ML, and data pipelines.

• Cultural Fit Interview: Assessment of alignment with the company's team-oriented and supportive culture.

Portfolio Review Tips:

• Highlight Relevant Projects: Showcase projects that directly align with the required skills (Python, PyTorch, AI/ML, data pipelines).

• Demonstrate Problem-Solving: Clearly articulate the challenges faced in projects and how they were overcome.

• Quantify Results: If possible, provide metrics on model performance or efficiency gains achieved.

• Code Quality: Ensure code in repositories is clean, well-commented, and demonstrates good programming practices.

Challenge Preparation:

• Python Fundamentals: Be prepared for questions on Python data structures, algorithms, and object-oriented programming.

• PyTorch Basics: Understand core concepts like tensors, autograd, model definition, and training loops.

• AI/ML Concepts: Be ready to discuss fundamental machine learning principles, especially related to object detection.

• Data Handling: Prepare to discuss experience with data extraction, transformation, and cloud storage.

📝 Enhancement Note: The interview process for a "Werkstudent" role will likely be less intensive than for a full-time position but will focus heavily on practical skills and learning potential.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Language: Python (3.10+)

• ML Framework: PyTorch

• Cloud Platforms: Google Cloud Platform (GCP), specifically BigQuery and Google Cloud Storage (GCS)

• API Development: REST APIs

• Web UI Development: Standard web technologies (specifics may vary)

Analytics & Reporting:

• Data Warehousing: BigQuery

• Experiment Tracking: Potentially tools like MLflow, Weights & Biases, or similar (MLOps focus).

CRM & Automation:

• Integration: Tools for connecting different systems and data sources.

• Version Control: Git (implied for code management).

📝 Enhancement Note: The technology stack is heavily skewed towards Python-based AI/ML development and cloud data services, reflecting the core requirements of the role.

👥 Team Culture & Values

Operations Values:

• Teamwork: Strong emphasis on mutual support and reliance within the team ("Wir isentos verstehen uns als Team").

• Customer Focus: Commitment to delivering the best solutions for clients.

• Quality: Dedication to high standards in software development and project execution.

• Growth & Development: Encouragement of individual learning and professional advancement.

• Respect: Fostering a friendly and respectful working atmosphere.

Collaboration Style:

• Agile & Iterative: Working in small, collaborative teams with frequent communication.

• Knowledge Sharing: Encouraging the exchange of ideas and best practices.

• Proactive Engagement: Encouraging interns to contribute ideas and take initiative.

📝 Enhancement Note: The company values are clearly articulated, emphasizing a collaborative and supportive environment that is attractive to students looking for a positive learning experience.

⚡ Challenges & Growth Opportunities

Challenges:

• Rapid Prototyping: Balancing speed of development with the need for robust and functional prototypes.

• AI Model Integration: Successfully integrating and fine-tuning complex AI models for specific tasks.

• Data Pipeline Complexity: Managing and transforming data from various sources efficiently.

• Cross-Platform Deployment: Navigating the complexities of deploying software across different operating systems and environments.

Learning & Development Opportunities:

• Hands-on AI/ML: Deepen practical skills in PyTorch and object detection through real-world application.

• Cloud Technologies: Gain experience with GCP services like BigQuery and GCS.

• Software Engineering Best Practices: Learn about secure software development and agile methodologies.

• Industry Insight: Understand client needs and project management in the IT consulting sector.

📝 Enhancement Note: The challenges are directly related to the technical demands of the role, offering valuable learning experiences for an intern.

💡 Interview Preparation

Strategy Questions:

• "Describe a challenging Python project you worked on and how you overcame the obstacles." (Focus on problem-solving and technical approach)

• "How would you approach building a prototype for object detection if you had limited labeled data?" (Assesses creativity and understanding of ML limitations)

• "Explain the concept of a custom training loop in PyTorch and why it might be necessary." (Tests fundamental PyTorch knowledge) Company & Culture Questions:

• "What interests you about working at isento GmbH specifically, and what do you know about our focus on AI and secure software development?" (Assesses research and genuine interest)

• "How do you prefer to collaborate with team members on technical projects?" (Evaluates teamwork and communication style)

• "How do you manage your time between academic studies and part-time work?" (Assesses organizational skills) Portfolio Presentation Strategy:

• Project Walkthrough: Be prepared to walk through one or two key projects from your portfolio, explaining the problem, your solution, the tools used, and the outcome.

• Code Examples: Be ready to discuss specific code snippets that demonstrate your proficiency in Python or PyTorch.

• Focus on Learning: Emphasize what you learned from each project and how it has prepared you for this role.

📝 Enhancement Note: Interview questions will likely probe both technical depth and the candidate's ability to integrate into the team and company culture.

📌 Application Steps

To apply for this operations position:

• Submit your application through the provided join.com link.

• Tailor Your CV: Highlight your experience with Python, PyTorch, AI/ML concepts, and any relevant cloud technologies. Quantify achievements where possible.

• Prepare Your Portfolio: Curate projects that best demonstrate your skills in prototyping, AI/ML, and data handling. Ensure code repositories are accessible and well-organized.

• Practice Technical Concepts: Review fundamental Python programming, PyTorch functionalities, and AI/ML principles, especially related to object detection.

• Research isento GmbH: Understand the company's mission, values, and focus areas (AI, secure software development) to articulate your interest and cultural fit.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

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