13 часов назад
AI Engineer (ML)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Engineer (ML): Building AI infrastructure, AI-driven applications, feature and model stores, and scalable tooling for multi-asset trading with an accent on production machine learning, MLOps, AIOps, and large language models. Focus on automating model training and monitoring, optimizing GPU and CPU usage, and deploying reliable AI systems from proof of concept to production.
Location: London, United Kingdom
Company
is a diversified trading firm using sophisticated technology and proprietary capital across global financial markets, with additional strategies in real estate, venture capital, and cryptoassets.
What you will do
- Develop AI infrastructure and AI-driven applications from proof of concept through production deployment and maintenance.
- Partner with technologists, traders, quantitative researchers, and data scientists to identify and implement high-impact AI and machine learning use cases.
- Build automated systems for continuous model training, validation, monitoring, and reliable operation.
- Select, integrate, and optimize AI and ML frameworks, libraries, and tools across varied hardware and software environments.
- Create feature pipelines, feature stores, model stores, and frameworks for scalable, reproducible research.
- Troubleshoot performance bottlenecks and optimize GPU and CPU resource usage through root-cause analysis.
Requirements
- Bachelor’s or advanced degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
- At least 3 years of experience working with machine learning and artificial intelligence technology.
- Strong understanding of core ML and AI concepts and excellent Python programming skills.
- Experience building, validating, deploying, monitoring, and updating production ML and AI models.
- Hands-on experience with MLOps and AIOps infrastructure and tooling.
- Experience with TensorFlow, PyTorch, TensorRT, or ONNX; Large Language Models, including RAG and fine-tuning; and AI/ML compute infrastructure.
Culture & Benefits
- Collaborative work with multi-asset trading, technology, quantitative research, and data science teams.
- High-autonomy environment with an emphasis on innovation, integrity, curiosity, and challenging consensus.
- Opportunity to work with cutting-edge technology and solve complex business and technology problems.
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