Develop and deploy scalable, production-grade machine learning and AI solutions for financial research. Build LLM- and NLP-based applications, collaborate with senior engineers, and contribute to reliable AI-driven products. Responsibilities require Python, software engineering, deep learning, databases, Docker, and at least one major deep learning framework. Preferred experience includes RAG pipelines, vector databases, LLM fine-tuning, cloud platforms, and Kaggle competitions.
Description
We are building scalable, production-grade AI systems that make high-quality financial research accessible and data-driven.
We are looking for a Data Science / AI Engineer to develop and deploy machine learning and AI solutions, with exposure to LLM-based systems and modern NLP applications. You will collaborate with senior engineers to build scalable and reliable AI-driven products.
RequirementsRequirements:
- 3+ years of commercial experience as a Data Science / AI Engineer
- Strong Python skills and solid software engineering fundamentals
- 1+ year of experience with LLM and NLP-related tasks
- Understanding of modern deep learning architectures
- Experience with at least one deep learning framework (TensorFlow or PyTorch)
- Experience with SQL and NoSQL databases
- Good knowledge of Docker
- Strong knowledge of object-oriented programming
- Fluency in Ukrainian
- Upper-Intermediate or higher level of English (spoken and written)
Nice to Have:
- Hands-on experience with RAG pipelines and vector databases
- Experience training or fine-tuning LLMs
- Experience with cloud platforms (AWS, Google Cloud, Azure)
- Participation in Kaggle or similar competitions
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