6 дней назад
Senior Machine Learning Engineer (LLM/NLP)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Machine Learning Engineer (LLM/NLP): Designing and integrating production ML and AI modules, including LLM-based systems, assistants, search, recommendation, and intelligent data processing, with an accent on end-to-end delivery, model evaluation, and MLOps. Focus on training and monitoring models, evaluating quality and failure cases, making architectural decisions, and building reliable high-load systems with CI/CD, containerization, and observability.
Location: Hybrid in Limassol, Tbilisi, or Paphos
Company
operates a financial analysis platform used by more than 100 million users across over 180 countries.
What you will do
- Design and implement ML and AI modules from experimentation and prototyping through production integration.
- Build LLM- and NLP-based solutions for data processing, generation, search, assistants, bots, agents, and automation.
- Prepare data, train models, run A/B tests, and analyze results.
- Monitor and improve model performance, reliability, latency, cost, and key metrics.
- Evaluate AI-system quality, investigate failure cases, and improve models, prompts, data, and architecture.
- Collaborate with product managers, engineers, and analysts while contributing to ML architecture and engineering standards.
Requirements
- 3+ years of experience in ML engineering and building production-ready ML systems.
- Strong practical expertise in NLP, LLMs, AI assistants, classification, ranking, retrieval, semantic similarity, and information extraction.
- Experience delivering end-to-end ML solutions from data and experimentation to production and support.
- Proficiency in Python and Go with production-grade development experience.
- Knowledge of A/B testing, result interpretation, architectural decision-making, and ML/AI quality evaluation.
- Familiarity with Docker, Kubernetes, CI/CD, monitoring tools such as Prometheus and Grafana, and logging.
Nice to have
- Experience with real-time and high-load ML systems.
- Experience with open-source or self-hosted models.
- Familiarity with MLflow, Airflow, Kubeflow, or similar MLOps tools.
- Product-oriented mindset and understanding of business metrics.
- Experience evaluating the UX of AI-driven interactions.
Culture & Benefits
- Flexible working hours and a hybrid work format.
- Well-equipped offices for focused and collaborative work.
- Learning, mentorship, and long-term career growth.
- Relocation support and private health insurance.
- Performance-based bonuses, Premium access, and regular team events.
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