Auf einen Blick
- Aufgaben: Tackle exciting ML and data engineering challenges while deploying models and optimizing performance.
- Arbeitgeber: Join a dynamic team focused on innovative solutions in machine learning and data science.
- Mitarbeitervorteile: Enjoy potential remote work options and the chance to work on cutting-edge technology.
- Warum dieser Job: This role offers hands-on experience with LLMs and collaboration across diverse teams.
- Gewünschte Qualifikationen: MS/PhD in relevant fields and strong programming skills in Python required.
- Andere Informationen: Fluency in German and English is essential for effective communication.
Das voraussichtliche Gehalt liegt zwischen 43200 - 72000 € pro Jahr.
Start date: asapPlanned duration: 12 monthsExtension: possibleYour tasks:Solve core ML and data engineering challenges, handling model deployment and relevant backend/frontend engineering; as well as model evaluation, and finetuning.Develop methods for semantic interpretation and automated redundancy removal of proprietary documents.Devise experiments to help our understanding of a good knowledge base for LLM Agents.Build pipelines that span data collection, document preparation and pre-processing, RAG implementation and LLM evaluation for different internal applications and use casesBenchmark and evaluate optimization techniques to ensure efficiency and performance.Familiarize yourself with diverse document sources and formats.Measure and analyze the pipeline’s performance, providing data-driven insights for improvement.Work closely with cross-functional teams, communicating results clearly to key stakeholders across RDI Operations to ensure the product’s reliability and project success.Your Profile:MS/PhD in Computer Science, Data Science, Statistics, (Computational) Linguistics or related fieldsExperience in machine learning or related fieldsDemonstrated technical capabilities in deploying and evaluating machine learning models in production environments or in ML/LLM researchStrong programming skills in Python and deep learning frameworks such as PyTorch, Tensorflow, JAXA dynamic and resilient individual who is open to work in an evolving project environment, taking initiative to shape the project, continuously learning and adapting to new challenges and opportunitiesGood communication skills, with the ability to effectively communicate technical concepts to both technical and non-technical audiencesFluent in German and English #J-18808-Ljbffr
Machine Learning Engineer / Data Scientist ROCGJP00029098 Arbeitgeber: Coopers Group GmbH
Kontaktperson:
Coopers Group GmbH HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Machine Learning Engineer / Data Scientist ROCGJP00029098
✨Tip Number 1
Make sure to showcase your experience with machine learning model deployment and evaluation. Highlight any specific projects where you've successfully implemented these skills, as this will resonate well with the hiring team.
✨Tip Number 2
Familiarize yourself with the latest trends in semantic interpretation and redundancy removal techniques. Being able to discuss recent advancements or methodologies in these areas during your interview can set you apart from other candidates.
✨Tip Number 3
Prepare to discuss your experience with cross-functional teams. Be ready to provide examples of how you've effectively communicated complex technical concepts to non-technical stakeholders, as this is crucial for the role.
✨Tip Number 4
Since the role requires fluency in both German and English, practice discussing your technical expertise in both languages. This will help you feel more confident during the interview and demonstrate your bilingual capabilities.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Machine Learning Engineer / Data Scientist ROCGJP00029098
Tipps für deine Bewerbung 🫡
Understand the Role: Make sure to thoroughly read the job description for the Machine Learning Engineer position. Understand the key responsibilities and required skills, especially in ML model deployment and data engineering.
Tailor Your CV: Customize your CV to highlight relevant experience in machine learning, data science, and programming skills in Python. Include specific projects or roles that demonstrate your capabilities in deploying ML models and working with deep learning frameworks.
Craft a Strong Cover Letter: Write a cover letter that connects your background to the job requirements. Emphasize your experience with semantic interpretation, document processing, and collaboration with cross-functional teams. Make sure to express your enthusiasm for the role and the company.
Showcase Communication Skills: In your application, provide examples of how you've effectively communicated technical concepts to diverse audiences. This is crucial for the role, as you'll need to convey results clearly to stakeholders across different teams.
Wie du dich auf ein Vorstellungsgespräch bei Coopers Group GmbH vorbereitest
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning models, especially in production environments. Highlight specific projects where you deployed or evaluated models, and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate Your Problem-Solving Abilities
Since the role involves solving core ML and data engineering challenges, think of examples where you've successfully tackled complex problems. Use the STAR method (Situation, Task, Action, Result) to structure your responses.
✨Communicate Clearly
You’ll need to communicate technical concepts to both technical and non-technical audiences. Practice explaining your past projects in simple terms, focusing on the impact and results rather than just the technical details.
✨Prepare for Behavioral Questions
Expect questions about teamwork and adaptability, as the role requires working closely with cross-functional teams. Reflect on past experiences where you demonstrated resilience and initiative in evolving project environments.