ML Engineer
Ailoys GmbH
Berlin, Germany
yesterday
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
IntermediateJob location
Berlin, Germany
Tech stack
Amazon Web Services (AWS)
Data analysis
Python
NumPy
TensorFlow
SciPy
PyTorch
Pandas
HuggingFace
Spacy
Requirements
- Expertise in the evaluation of generative AI methods.
- A good understanding of statistics and data analysis.
- Data annotation management.
- Practical Python language skills.
- Familiarity with frameworks such as NumPy, SciPy, pandas, and Hugging Face Evaluate.
- A minimum of 2-3 years of relevant work experience is required.
Nice to have:
- ML frameworks, such as PyTorch, spaCy, and Transformers.
- CI, workflow automation, and experiment tracking systems.
- Familiarity with the AWS Bedrock
Benefits & conditions
- A competitive salary that recognizes your skills and contributions.
- Work on cutting-edge technologies in industrial AI, IoT and manufacturing automation.
- Be part of a fast-growing, innovative team with opportunities for professional growth.
- Contribute to impactful projects with leading global manufacturing companies.
If you are passionate about driving innovation in manufacturing and have the technical expertise to match, we'd love to hear from you!
About the company
At Ailoys GmbH, we are transforming the manufacturing landscape by integrating advanced technologies like IoT, sensor systems, AI and machine learning. Our mission is to empower manufacturing facilities with smarter processes, improved quality, and enhanced efficiency.
We are looking for a Machine Learning (ML) Engineer who will focus on researching appropriate models for automation manufacturing processes.
In this role, you will:
* Design and develop evaluation benchmark.
* Deploy end-to-end evaluation pipelines for in-house and external ML models.
* Be responsible for model selection and comparison with state-of-the-art methods.
* Analyze evaluation results and propose improvements to data and models.