Senior Machine Learning Engineer

TradingView is the world’s largest financial analysis platform with more than 100M users across 180+ countries.

We build tools that help traders and investors make informed decisions — from advanced charting and market data to collaboration and publishing features. Our products are used daily by millions of individuals and trusted by companies like Revolut, Binance, and CME Group.

We’re continuing to grow and scale our platform, and we’re looking for people who care about product quality, take ownership of their work, and want to build systems used by a global audience.

About the team

We develop and implement machine learning and AI solutions across a range of products: AI assistants, customer support chatbots, intelligent data processing, generative AI features, recommender systems, spam detection, search and other ML-powered modules.

Our goal is to build reliable ML and AI systems that solve real product problems — from experimentation and prototyping to production integration and continuous improvement.

Responsibilities

•Designing and implementing ML and AI modules for various products, from experimentation and prototyping to production integration

•Building solutions based on LLMs and other ML/NLP approaches for data processing, generation, search, assistants, bots, agents and automation

•Choosing and evaluating appropriate approaches — including external AI providers, open-source or self-hosted models, as well as traditional ML/NLP methods

•Contributing to the architecture of ML solutions, shaping technical approaches and engineering standards

•Preparing and processing data, training models, running A/B tests, and analyzing results

•Monitoring and improving model performance, interpreting model behavior and key metrics

•Evaluating AI-system quality, analyzing failure cases and improving models, prompts, data and system architecture

•Collaborating with product managers, engineers, and analysts to clarify requirements, integrate solutions, and evaluate their impact

•Working with MLOps infrastructure: CI/CD, monitoring, logging, containerization

What makes you the perfect fit

•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 both modern LLM-based systems and traditional ML/NLP approaches such as classification, ranking, retrieval, semantic similarity and information extraction

•Strong track record of delivering end-to-end ML solutions — from idea and data to production and support

•Proficient Python skills and experience with production-grade development

•Experience evaluating ML/AI solutions and understanding their quality, reliability, latency and cost trade-offs

•Solid knowledge of A/B testing and result interpretation

•Experience in architectural decision-making and a drive to improve engineering practices …

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