Senior Machine Learning Engineer
TradingView13 days ago
Limassol, CyprusSenior
Responsibilities
- Design and implement ML and AI modules from experimentation and prototyping through production integration.
- Build LLM- and ML/NLP-based solutions for data processing, generation, search, assistants, bots, agents, and automation.
- Select and evaluate external providers, open-source or self-hosted models, and traditional ML/NLP approaches.
- Contribute to ML solution architecture, technical approaches, and engineering standards.
- Prepare and process data, train models, run A/B tests, and analyze results.
- Monitor and improve model performance, interpret model behavior, and analyze key metrics.
- Evaluate AI-system quality, investigate failure cases, and improve models, prompts, data, and system architecture.
- Collaborate with product managers, engineers, and analysts to clarify requirements, integrate solutions, and evaluate impact.
- Work with MLOps infrastructure including monitoring, logging, containerization, and CI/CD systems.
Requirements
- 3+ years of experience in ML engineering and building production-ready ML systems.
- Strong practical expertise in NLP, LLMs, AI assistants, and related AI/ML areas.
- Experience with modern LLM-based systems and traditional ML/NLP approaches such as classification, ranking, retrieval, semantic similarity, and information extraction.
- Track record of delivering end-to-end ML solutions from idea and data through production and support.
- Proficiency in Python and Go with experience in production-grade development.
- Experience evaluating ML/AI solutions and understanding quality, reliability, latency, and cost trade-offs.
- Solid knowledge of A/B testing and result interpretation.
- Experience with architectural decision-making and improving engineering practices.
- Familiarity with Docker, Kubernetes, monitoring tools such as Prometheus and Grafana, logging, and CI/CD systems.
- Preferred: product-oriented mindset, understanding of business metrics, real-time or high-load ML systems experience, open-source or self-hosted model experience, modern MLOps tools, and UX evaluation of AI-driven interactions.
Benefits
- Flexible working hours and a hybrid work format.
- Well-equipped offices for focused and collaborative work.
- Global, distributed team of 500+ professionals.
- Learning, mentorship, and long-term career growth.
- Relocation support and private health insurance.
- Performance-based bonuses.
- TradingView Premium access.
- Regular team events and company-wide meetups.
Tech Stack
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