Machine Learning Engineer
At Corsearch · Finland (Helsinki); Helsinki, Finland
- Data and ML
- Temporary
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Where you’ll work
Hybrid, based in Helsinki
“Finland (Helsinki)”
From the location.
“Helsinki, Finland”
From the job board field.
“Location: Helsinki/ 2 days Hybrid”
From the job description.
The job board lists it as hybrid.
Hybrid means some days in the office. The listing says how many, and where.
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- Posted
- 24 August 2026
- First seen by us
- 15 October 2026
- Last checked
- 29 hours ago
Job description
From Corsearch’s job post, as they wrote it.
Reporting to: Principal Data Scientist
Location: Helsinki/ 2 days Hybrid
About the Role:
We're looking for a passionate and skilled Machine Learning Engineer to enhance and evolve our trademark search engine. In this role, you'll explore and implement state-of-the-art NLP and CV architectures tailored to the complex domain of trademark search.
This role is a 9-months fixed term contract maternity cover for part-time hours of 2.5 days per week.
Read the full description
Key Responsibilities in this Role:
* Design and implement transformer-based pipelines for data processing and enhancement across diverse applications
* Collaborate with other ML engineers on NLP and multi-modal tasks
* Build and maintain robust, production-grade APIs
* Monitor, evaluate, and optimize machine learning models deployed in production environments
* Apply, fine-tune, and develop pretrained LLMs and VLMs for trademark search and analysis
* Conduct research and experimentation to improve neural network architectures and model performance
* Design and maintain scalable data pipelines and experimentation frameworks
What are we looking for
* Proven experience in end-to-end NLP and/or Computer Vision (CV) pipelines
* Strong software engineering skills: Python, Pytest, Docker, mypy, algorithmic complexity
* Proficient with PyTorch, Hugging Face Ecosystem, and xTransformers
* Deep knowledge of modern neural architectures: Transformers, RNNs, BLIP, LLMs, VLMs, CLIP
Additional desirable experience
* Experience with vision-language models: LLaVA, Phi-3 Vision, Qwen-VL, OpenCLIP
* Familiarity with AWS services: IAM, SageMaker, EC2 spot instances, S3, CloudWatch
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