What you’ll do
You will be a key figure in our Engineering Department, responsible for operationalizing innovative methods and solutions derived from our own R&D as well as the latest AI/LLM technologies.
You will be responsible for leveraging machine learning libraries and frameworks to create and fine-tune models that can understand and produce language based on prompts.
The Engineering Department is dedicated to delivering commercial-quality solutions as the final product. While focusing on delivering these solutions, we remain committed to periodically revisiting research activities to ensure a continual synergy between our engineering efforts and ongoing research endeavors. We work both on big in-house projects as well as cooperate with partners in specific implementations.
What you need to know
- 3 years of experience in machine learning in python
- deep understanding of neural networks with focus on generative LLM
- experience in prompt engineering
- knowledge of OpenAI REST API and their python package
- understanding of asynchronous programming paradigm
Nice to have
- experience in audio signal processing for analyzing and generating audio content. Knowledge of models that can generate speech or music would be beneficial.
- proficiency in pydantic and instructor
- NLP knowledge especially spacy/gensim packages
- understanding of backend RESTful frameworks especially fastapi
- experience with NoSQL databases especially DynamoDB
- experience with AWS machine learning and ETL stack
- familiarity with web scraping, e.g. css selectors, html tags
- experience with Computer Vision: knowledge of CV libraries and frameworks (e.g., OpenCV, TensorFlow, or PyTorch)
- familiarity with generative models for images and video: understanding of generative models beyond text, such as GANs and VAEs
- deep understanding of RAG architecture and experience in fine-tuning RAG models for specific domains or tasks
We offer:
- market-based salary adjusted to your skills;
- flexible working hours;
- 26 days of paid leave
- partially remote
- internal trainings;
- 10% of work time for self-development;