We're looking for a Senior ML-Engineer to lead the development of machine learning systems that directly influence product performance. With over five years of experience in production ML, you'll collaborate across multiple teams to design and deploy models that solve complex business challenges—from optimizing donation flows to building intelligent pipelines powered by large language models.
What You'll Do
- Design, train, and deploy machine learning models using tabular data, including uplift modeling and recommendation systems
- Evaluate problem spaces and determine whether ML, classical algorithms, or alternative approaches offer the best path forward
- Own the full lifecycle of ML development: data extraction, feature engineering, model training, API integration, and monitoring in production
- Develop and refine prompt-based workflows using LLM APIs to support classification, content generation, and response evaluation tasks
What We're Looking For
- Proven experience solving product-driven challenges with machine learning over a 5+ year span
- Deep understanding of core ML techniques and statistical foundations, with strong command of gradient-boosted models
- Ability to align model performance metrics—like AUC, F1, or RMSE—with tangible business outcomes such as conversion rate or customer lifetime value
- Strong software engineering skills in Python, with an emphasis on maintainable, testable, and scalable code
- Proficiency in SQL and hands-on experience building datasets in ClickHouse and MongoDB
- Familiarity with MLOps practices, including experiment tracking, containerization with Docker, version control, and CI/CD pipelines
- Self-direction and problem-solving ability—able to decompose tasks, choose appropriate tools, and deliver working solutions to production
Preferred Background
- Experience in natural language processing or related NLP applications
Technology Environment
Our stack includes Python (with uv and ruff), FastAPI, Pydantic, Docker, CatBoost, CausalML for uplift modeling, OpenAI APIs with RAG and prompt engineering, ClickHouse, MongoDB, pandas, Polars, Redis, MLflow, Airflow, Grafana, and Sentry.
Work & Culture
We operate fully remotely with team members across Armenia, Spain, Serbia, Poland, Portugal, Turkey, Cyprus, and Georgia. The role offers complete flexibility, with no office requirement. Our culture is built on technical excellence, open communication, and shared growth. Engineers regularly host bi-weekly meetups to exchange insights and explore new ideas. We maintain a flat structure—no bureaucracy, just meaningful work and mutual support.
Transparency is core: we share revenue data, growth metrics, and strategic direction openly. We're focused on long-term impact, not short-term wins.
Benefits
- 31 days of annual leave
- Full coverage telemedicine plan
- Support for home office setup, including ergonomic furniture and equipment
- Access to English language courses
- Funding for professional development and technical education
- Gym or swimming pool membership
- Co-working space access when desired
- Remote-first work model
Compensation
This role includes equity options as part of the total compensation package.
