Position: Data Science/Machine Learning Engineer
Company: ScrumLaunch
Category: Data Science
Experience required: 2y
English level: upper

We are looking for ML engineer that will own the build and maintenance of data and ML pipelines. At the core of a product is invoice digitization to transform invoice data, for example, locked away in PDFs, into a rich and clean digital data asset. And our ideal candidate can make it reality, and also monitor and maintain our products.

Responsibilities:

- Perform inference using existing NLP and computer vision mode
- Use human-in-the-loop annotations to automatically retrain and deploy updated models
- Monitor and maintain the models in production over time
- Refactor code form data scientists to push into production
- Architect and deliver new pipelines to enrich invoice data from our machine learning models
- Make models available as APIs

Requirements:

- 3+ years of Python and SQL
- 2+ years of main machine learning algorithms (classification, regression, prediction)
- Experience with NLP libraries, such as scikit-learn, PySpark, spaCY, NLTK, TextBlob
- Experience with AWS (S3, Lambda, API Gateway, SageMaker, Step Functions)
- Experience with debugging
- Organized with a high attention to detail
- Ensure application performance, uptime, and scale, maintaining high standards of code quality and thoughtful application design
- Good written and verbal communication skills
- Upper Intermediate English level

Additional:

- Experience with СV(Computer Vision) libraries: OpenCV, Tensor, Keras, scikit-image.
- Building ETL/ML pipelines with GCP, AWS, Dataricks etc.
- Working and building APIs

**Additional:**

— Experience with СV(Computer Vision) libraries: OpenCV, Tensor, Keras, scikit-image.
— Building ETL/ML pipelines with GCP, AWS, Dataricks etc.
— Working and building APIs

**We offer:**

— Opportunity to grow as an expert;
— Regular results-based salary review;
— Flexible working conditions;
— 24 days of paid vacation;
— 10 sick days;
— Office in the city center;
— Friendly and open-minded team;
— English classes;
— Relax and fun zones.