Senior Data Scientist – LLMs, RAG, Multimodal AI
Proximity Works
PythonPyTorchTensorflow
Job Level
JuniorMid-Level
Tech Stack
PyTorch
About the role
- Design, implement, and fine-tune systems incorporating large language models (LLMs) and other advanced AI techniques for applications such as sentiment analysis, news aggregation, market predictions and data cleaning
- Work with structured and unstructured datasets to train models that generate insights and forecasts for investment strategies
- Continuously enhance performance and efficiency of LLMs to ensure scalability and resource-efficiency
- Partner with portfolio quant researchers to develop models addressing market opportunities and challenges
- Stay abreast of latest NLP and LLM developments and contribute to internal thought leadership
- Deploy machine learning models in production, integrating with existing infrastructure and real-time market data feeds
- Identify risks related to LLMs and implement safeguards for model bias and robustness
Requirements
- Minimum 2 years of hands-on experience working with LLMs, NLP or deep learning in a high-performance environment
- Experience working with large-scale datasets and deploying machine learning models in production
- Knowledge of modern NLP techniques and frameworks (e.g., tokenizers, transformers, embedding models)
- Familiarity with machine learning platforms and tools (e.g., PyTorch, HuggingFace, OpenAI)
- Strong understanding of algorithmic trading and financial data is a plus
- Excellent problem-solving abilities, with the capacity to translate complex business requirements into innovative technical solutions
