Susquehanna International Group
Machine Learning Researcher - LLM
Susquehanna International Group, Narberth, Pennsylvania, United States, 19072
Overview
Our Machine Learning team is expanding into large language models (LLMs), and we’re looking for bold, inventive minds to help us push the boundaries of generative AI.
As a Deep Learning Researcher, you will work on some of the most ambitious challenges in the LLM space: aligning models with human intent, optimizing training at scale, and deploying intelligent systems that operate in real-time, high-stakes environments. You will have access to extensive, high-quality proprietary datasets.
You’ll have the autonomy to explore novel ideas, the resources to scale them, and the opportunity to see your research power real-world trading systems.
What You’ll Do
Lead and contribute to research initiatives that advance LLM capabilities, including alignment, fine-tuning, and efficient training
Design and execute large-scale experiments, from data pre-processing to model evaluation and deployment
Collaborate with world-class engineers, traders, and researchers to bring ideas from prototype to production
Optimize model performance for structured tasks such as function calling, multilingual applications, and real-time inference
What we’re looking for
PhD in Computer Science, Machine Learning, or a related field—or equivalent practical experience
Experience in ML research or engineering, with a focus on deep learning or generative models
A strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR
Strong background in modern language modeling techniques such as LLM supervised fine-tuning, RLHF, reasoning models, embedding models, multimodal models, or agentic architectures
Proficiency in Python and ML frameworks such as PyTorch (preferred), TensorFlow, or JAX
Experience with large-scale distributed training, GPU optimization (CUDA/ROCm), or HPC environments
Experience designing and operating large-scale data annotation and curation pipelines, including labeling tools, workflow orchestration, quality-control auditing, and learning feedback loops
Demonstrated ability to take research from conception to production in high-stakes environments
Strong communication skills and a collaborative mindset
If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.
Our Machine Learning team is expanding into large language models (LLMs), and we’re looking for bold, inventive minds to help us push the boundaries of generative AI.
As a Deep Learning Researcher, you will work on some of the most ambitious challenges in the LLM space: aligning models with human intent, optimizing training at scale, and deploying intelligent systems that operate in real-time, high-stakes environments. You will have access to extensive, high-quality proprietary datasets.
You’ll have the autonomy to explore novel ideas, the resources to scale them, and the opportunity to see your research power real-world trading systems.
What You’ll Do
Lead and contribute to research initiatives that advance LLM capabilities, including alignment, fine-tuning, and efficient training
Design and execute large-scale experiments, from data pre-processing to model evaluation and deployment
Collaborate with world-class engineers, traders, and researchers to bring ideas from prototype to production
Optimize model performance for structured tasks such as function calling, multilingual applications, and real-time inference
What we’re looking for
PhD in Computer Science, Machine Learning, or a related field—or equivalent practical experience
Experience in ML research or engineering, with a focus on deep learning or generative models
A strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR
Strong background in modern language modeling techniques such as LLM supervised fine-tuning, RLHF, reasoning models, embedding models, multimodal models, or agentic architectures
Proficiency in Python and ML frameworks such as PyTorch (preferred), TensorFlow, or JAX
Experience with large-scale distributed training, GPU optimization (CUDA/ROCm), or HPC environments
Experience designing and operating large-scale data annotation and curation pipelines, including labeling tools, workflow orchestration, quality-control auditing, and learning feedback loops
Demonstrated ability to take research from conception to production in high-stakes environments
Strong communication skills and a collaborative mindset
If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.