Internship - Machine Learning Research Engineer
Primary stack
PyTorch
Job description
About the Position
Internship - Machine Learning Research Engineer
Berlin
Internship Program Berlin
Internship program: 12 - 24 weeks, full-time, in-person in the Berlin office.
Responsibilities
- Relentlessly push search quality forward - through models, data, tools, or any other leverage available.
- Train, and optimize large-scale deep learning models using frameworks like PyTorch, leveraging distributed training (e.g., PyTorch Distributed, DeepSpeed, FSDP) and hardware acceleration, with a focus on retrieval and ranking models.
- Conduct research in representation learning, including contrastive learning, multilingual, evaluation, and multimodal modeling for search and retrieval.
- Build and optimize RAG pipelines for grounding and answer generation.
Requirements
- Understanding of search and retrieval systems, including quality evaluation principles and metrics.
- Strong proficiency with PyTorch, including experience in distributed training techniques and performance optimization for large models.
- Interested in representation learning, including contrastive learning, dense & sparse vector representations, representation fusion, cross-lingual representation alignment, training data optimization, and robust evaluation.
- Publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, SIGIR).
We Offer
- Opportunity to work in a leading tech company in Berlin
- Hands-on experience with state-of-the-art machine learning techniques
- Mentorship from experienced researchers and engineers
- Networking opportunities with professionals in the field
About the Company
[Company description if present]
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