RedLab is a global IT company.
We unite talents to develop digital solutions and products that meet high quality standards for the country's most ambitious IT projects.
You can gain experience and unlock your potential by working on unique technological projects for our clients.
You focus on technical tasks, and we handle negotiations with the client, resolving bureaucratic issues, and ensuring timely payment for project work.
We are inviting an ML Engineer to work on our clients' IT projects (in an outstaff format).
We will entrust you with:
- Researching and applying mathematical and ML methods to solve applied business problems, selecting optimal algorithms based on data specifics and goals;
- Developing and training ML models (RecSys, churn models, Uplift, Propensity, NLP/NER, LLM/RAG solutions);
- Building end-to-end ML pipelines: from hypothesis testing and data analysis to training, validation, and selecting the best models or ensembles;
- Implementing production-ready solutions: preparing models for deployment, optimizing inference (speed, stability, scalability);
- Integrating ML solutions into existing IT infrastructure (APIs, message brokers, data storage);
- Optimizing the performance and scalability of ML solutions for high-load systems;
- Setting up monitoring for technical and quality metrics of models;
- Collaborating with engineers, analysts, and product teams.
To perform the tasks, you need:
- Commercial development experience in Machine Learning for 3+ years;
- Python — advanced level (5+ years), ability to write clean and maintainable production code (OOP, SOLID);
- Knowledge of FastAPI/Django/Flask frameworks;
- Deep understanding of the theoretical foundation of ML: main tasks, methods, metrics, mathematical statistics, and probability theory;
- Practical experience with classical ML and boosting: Scikit-learn, CatBoost, XGBoost, LightGBM;
- Experience working with deep learning and NLP: PyTorch, Hugging Face Transformers;
- NLP/NER tasks, working with textual data;
- Experience in building and operating LLM and RAG pipelines;
- Practical work with LLM tools and agent frameworks: LangChain, LangGraph (or similar);
- Experience preparing models for production;
- Docker, CI/CD;
- Good knowledge of Linux;
- Experience with vector databases: Pinecone/Weaviate/Qdrant/pgvector;
- Ability to work with message brokers (Kafka/RabbitMQ);
- Understanding of MLOps principles and monitoring (including Grafana).
We offer:
- Remote work - the opportunity to work from any city;
- Timely payments;
- Interesting and unique IT projects in large companies.
- Discounts from partners - English language, training, shopping;
- Corporate library.
