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- Aufgaben: Join us as an ML Intern to tackle cutting-edge machine learning challenges in document understanding.
- Arbeitgeber: Be part of CONXAI, a dynamic start-up revolutionizing the AEC industry with AI technology.
- Mitarbeitervorteile: Enjoy a vibrant work culture with team events, after-work activities, and opportunities for personal impact.
- Warum dieser Job: This role offers hands-on experience with advanced ML models and collaboration with talented engineers.
- Gewünschte Qualifikationen: Pursuing a PhD/Master's in Computer Science; experience with PyTorch, document understanding, and Python required.
- Andere Informationen: Must be eligible to work in Germany and fluent in English.
We are developing an AI Platform for the Architecture, Engineering, and Construction (AEC) industry. Our platform leverages advanced AI to enable construction domain experts to create complex use cases efficiently.
Tasks
We are looking for full-time interns (for min. 6 months) to solve some cutting-edge machine learning problems and be a part of our product development.
You should have experience in implementing machine learning models in PyTorch, and be proficient in Python. Prior experience in document understanding, information extraction, OCR / OCR-free methods, or Retrieval Augmented Generation (RAG) with large-language models would be preferred.
The successful candidate will:
- Extract and pre-process data from transactional documents with varying layouts
- Collaborate with ML engineers on model design, experimentation and implementation
- Collaborate with ML engineers to design a system with state-of-the-art ML components that effectively addresses customer KPIs
- Discuss requirements with customer-facing members to understand the problem and its constraints
- Proactively propose and implement iterative improvements
- Propose and implement metrics to evaluate relevant KPIs
- Integrate the solutions to a common codebase and demonstrate good software engineering practices
- Communicate results and analysis on regular basis
Requirements
- Pursuing a PhD / Master’s degree in Computer Science or a related field enrolled in a German or EU university
- Experience in implementing machine learning models in PyTorch, specifically Large Language Models
- Experience with document understanding
- Experience with Retrieval Augmented Generation (RAG)
- Experience with OCR methods, OCR-free document understanding methods, e.g., Visual Document Question Answering (visual doc-QA) and Information Extraction
- Proficient in Python and good software engineering skills
- Good communication and interpersonal skills
- Ability to work in a team-oriented environment
- Strong problem-solving skills
- Fluent in English
- Eligible to work in Germany
Benefits
You will be a part of an inclusive start-up culture in a stimulating „work hard, play hard“ environment. You will work with (and party with) great colleagues with diverse backgrounds. Team events and after-work activities are frequent at CONXAI. You will be empowered to bring new perspectives and create impact.
ML Interns - Natural Language Processing: Document Understanding Arbeitgeber: Conxai Technologies GmbH
Kontaktperson:
Conxai Technologies GmbH HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: ML Interns - Natural Language Processing: Document Understanding
✨Tip Number 1
Familiarize yourself with the latest advancements in Natural Language Processing, especially in document understanding and Retrieval Augmented Generation. This will not only help you during interviews but also show your genuine interest in the field.
✨Tip Number 2
Engage with the community by participating in relevant forums or attending meetups focused on machine learning and AI. Networking can lead to valuable insights and connections that might help you land the internship.
✨Tip Number 3
Consider working on personal projects or contributing to open-source projects that involve PyTorch and document understanding. This hands-on experience will make you stand out and demonstrate your practical skills.
✨Tip Number 4
Prepare to discuss your previous experiences with machine learning models and how you've tackled challenges in your projects. Being able to articulate your problem-solving process will impress the interviewers.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: ML Interns - Natural Language Processing: Document Understanding
Tipps für deine Bewerbung 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning models, especially in PyTorch and document understanding. Include specific projects or coursework that demonstrate your skills in these areas.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background in computer science and your experience with OCR methods and Retrieval Augmented Generation align with the job requirements.
Showcase Relevant Projects: If you have worked on any relevant projects, especially those involving large language models or information extraction, be sure to mention them. Provide links to your GitHub or any other portfolio where they can see your work.
Highlight Team Collaboration Skills: Since the role involves collaboration with ML engineers and customer-facing members, emphasize your teamwork and communication skills. Share examples of how you've successfully worked in a team-oriented environment.
Wie du dich auf ein Vorstellungsgespräch bei Conxai Technologies GmbH vorbereitest
✨Showcase Your Technical Skills
Be prepared to discuss your experience with PyTorch and Python in detail. Bring examples of projects where you've implemented machine learning models, especially those related to document understanding or OCR methods.
✨Understand the AEC Industry
Familiarize yourself with the Architecture, Engineering, and Construction (AEC) industry. Understanding the specific challenges and use cases in this field will help you demonstrate your interest and relevance during the interview.
✨Prepare for Collaborative Scenarios
Since collaboration with ML engineers is key, think of examples from your past experiences where you successfully worked in a team. Be ready to discuss how you approach problem-solving and iterative improvements in a collaborative environment.
✨Communicate Clearly and Effectively
Good communication skills are essential. Practice explaining complex technical concepts in simple terms, as you may need to discuss requirements with customer-facing members. Clear communication can set you apart from other candidates.
