Senior ML Engineer

This is an opportunity to join the Search and Recommendations team as an ML Engineer.

Data Scientists train models within the scope of an experiment – they select the data for training, vary the model parameters. After obtaining a model of acceptable quality, they fix the parameters and hand it over to us.

ML Engineers optimize and automate training – they prepare the data pipeline for production infrastructure (so that it doesn't consume a lot of memory and runs as fast as possible), and transfer the training to specific tools so that it is repeatable and reproducible as envisioned by the Data Scientists.

We are looking for an ML Engineer.

• Development of Recommender Systems (Recsys) services using ML;
• Designing the architecture of ML services;
• Building ML pipelines (training, deployment, model updates);
• Implementing and supporting ML models in production;
• Optimizing inference and performance;
• Participation in code reviews and mentoring.

• ML experience of 4–5 years, of which ≥ 1 year with recommender systems in production;
• Experience with the full ML lifecycle: from prototype to production. Experience in designing ML service architectures;
• Knowledge of Recsys algorithms: collaborative filtering, matrix factorization, two-tower, sequence models
• Experience implementing MLOps practices and platforms in a team ( MLflow or similar);
• Proficient development in Python (FastAPI, asyncio);
• Solid SQL skills;
• Experience working with Docker and Kubernetes for deploying and orchestrating ML applications;
• Experience setting up comprehensive monitoring (Grafana, Prometheus) for models and infrastructure;
• Inference optimization skills (GPU, batching, Triton);
• Mentoring and code review experience

• Hybrid or remote work format, at your choice;
• After the probationary period: voluntary medical insurance with dental care, "Dobroservis" with unlimited legal and psychological consultation, fitness. Permanent discounts from our partners and much more;
• Payment for specialized courses, conference participation;
• Fun and memorable corporate events in nature and in the office: we play board games. We order pizza every last Friday of the month;
• Unlimited access to all e-books and audiobooks :)