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- Aufgaben: Tackle exciting ML and data engineering challenges while deploying models and optimizing performance.
- Arbeitgeber: Join Flexsis, part of the Interiman Group, a top personnel service provider in Switzerland.
- Mitarbeitervorteile: Enjoy remote work options, flexible hours, and the chance to work with cutting-edge technology.
- Warum dieser Job: Be part of innovative projects at Roche Diagnostics, making a real impact in the tech world.
- Gewünschte Qualifikationen: MS/PhD in relevant fields and at least one year of industry experience required.
- Andere Informationen: Fluent in German and English? This role is perfect for you!
Das voraussichtliche Gehalt liegt zwischen 43200 - 72000 € pro Jahr.
Flexsis is part of the Interiman Group, one of the leading providers of personnel services in Switzerland. Thanks to our solid expertise and the competences within the Interiman Group, we offer tailor-made solutions in personnel consulting.
For our client Roche Diagnostics in Rottkreuz , we are looking for a motivated and reliable (m/f/d)
Machine Learning Engineer / Data Scientist 70-100%
- 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 preprocessing, RAG implementation and LLM evaluation for different internal applications and use cases.
- Benchmark 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.
Minimum Requirements:
- MS/PhD in Computer Science, Data Science, Statistics, (Computational) Linguistics or related fields.
- Min. one year of industry experience in machine learning or related fields.
- Demonstrated technical capabilities in deploying and evaluating machine learning models in production environments or in ML/LLM research.
- Strong programming skills in Python and deep learning frameworks such as PyTorch, Tensorflow, JAX.
- A 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 opportunities.
- Good communication skills, with the ability to effectively communicate technical concepts to both technical and non-technical audiences.
- Fluent in German and English.
Start date: as soon as possible – latest 16.04.2025
Planned duration: 1 year
Extension: yes, possible
Remote/Home Office: up to 2 days a week
Are you interested and would you like to seize this opportunity? Then we should definitely get to know each other! Simply click on „Apply now“ and we look forward to receiving your complete application documents.
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Machine Learning Engineer / Data Scientist Arbeitgeber: FLEXSIS
Kontaktperson:
FLEXSIS HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Machine Learning Engineer / Data Scientist
✨Tip Number 1
Make sure to showcase your experience with deploying machine learning models in production environments. Highlight specific projects where you've successfully implemented ML solutions, as this will resonate well with the requirements of the role.
✨Tip Number 2
Familiarize yourself with Roche Diagnostics and their work in the healthcare sector. Understanding their products and challenges can help you tailor your discussions during interviews and demonstrate your genuine interest in contributing to their mission.
✨Tip Number 3
Brush up on your programming skills, especially in Python and deep learning frameworks like PyTorch and TensorFlow. Being able to discuss your coding experience and problem-solving approaches will be crucial in technical interviews.
✨Tip Number 4
Prepare to discuss how you communicate complex technical concepts to non-technical stakeholders. This is a key aspect of the role, so having examples ready will show that you can bridge the gap between technical and non-technical teams effectively.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Machine Learning Engineer / Data Scientist
Tipps für deine Bewerbung 🫡
Understand the Role: Make sure to thoroughly read the job description for the Machine Learning Engineer / Data Scientist 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 achievements that demonstrate your capabilities in deploying ML models and working with deep learning frameworks.
Craft a Strong Cover Letter: Write a compelling cover letter that showcases your motivation for the role and how your background aligns with the requirements. Emphasize your ability to communicate technical concepts clearly and your experience in collaborative environments.
Prepare for Technical Questions: Be ready to discuss your technical expertise during the interview process. Prepare to explain your experience with ML models, data pipelines, and any relevant projects you've worked on, as well as your approach to problem-solving in evolving project environments.
Wie du dich auf ein Vorstellungsgespräch bei FLEXSIS 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 and evaluated models, and be ready to dive into the technical details, including the frameworks you've used like PyTorch or TensorFlow.
✨Communicate Clearly
Since the role requires explaining complex concepts to both technical and non-technical audiences, practice articulating your thoughts clearly. Use simple language when necessary and ensure you can explain your work in a way that everyone can understand.
✨Demonstrate Problem-Solving Skills
Prepare to discuss how you've tackled challenges in previous projects. Think of specific examples where you devised experiments or optimized processes, and be ready to explain your thought process and the outcomes.
✨Familiarize Yourself with the Company’s Work
Research Roche Diagnostics and their projects related to machine learning and data science. Understanding their goals and challenges will help you tailor your responses and show your genuine interest in contributing to their success.
