REQUIREMENTS
- A minimum of 4 years of hands-on experience in production projects as a Machine Learning Engineer, Data Engineer, or Data Scientist.
- At least 5 years of overall experience in software development.
- Strong experience in Python programming language.
- Strong experience in PyTorch or Tensorflow.
- Strong experience in NLP and/or CV (not only GPT & BERT-like models).
- Strong experience with the following libraries: numpy, pandas, opencv, spacy, nltk, scikit-learn.
- Experience with generative models (GPT) and prompt engineering.
- English language (Intermediate and higher).
- This is a full-time position requiring exclusive commitment.
GOOD TO HAVE:
- Experience with Azure Cloud services (or alternative).
- Experience with OpenAI platform (or alternative).
- Experience with HuggingFace.
- Experience with data processing pipelines.
- Knowledge of data analysis, statistics and data visualisation (descriptive statistics, statistical tests, plotting, dashboards, etc.).
RESPONSIBILITIES:
- Automatization of information extraction from digital born and scanned documents in various formats (PDF, Excel, Word, Images etc.).
- Building prediction and recommendation models based on the input data and user behaviour.
- Building ML/data pipelines and datasets according to business requirements.
- Analysing and visualising the data and presenting the result to the team.
Top Skills
What We Do
We specialize in transforming Revenue Operations through advanced technological integration, combining AI, analytics, and strategic workflow automation.
Our core competency lies in developing comprehensive revenue optimization strategies that unify critical business functions including marketing, sales, billing, enterprise resource planning, and revenue recognition.
Leveraging SAP and other vendors' enterprise technologies we deliver sophisticated solutions that enable organizations to:
- Develop strategic outcome-based business models
- Implement enterprise-wide digital transformation
- Optimize complex revenue management processes
- Minimize implementation risks and operational costs
Our approach is distinguished by:
1. Comprehensive industry expertise
2. Advanced technological architecture
3. Proven deployment methodologies
4. Balanced focus on long-term strategic planning and immediate operational improvements
We collaborate with clients to design precision-engineered revenue ecosystems that align technological capabilities with strategic business objectives, ensuring sustainable growth and operational efficiency.
Expertise Areas:
1. Intelligent Revenue Operations (iRevOps)
2. Enterprise Technology Integration
3. Strategic Digital Monetization
4. AI-Enhanced Business Process Optimization
Our methodological framework transforms complex business requirements into streamlined, data-driven operational strategies.
