Machine Learning Researcher - LLM

SIG Susquehanna; Bala Cynwyd (PA); On-site; USD 120,000 - 180,000; Full time

Job summary

A leading company in financial technology is seeking a Deep Learning Researcher to join their expanding Machine Learning team. You will tackle ambitious challenges in the LLM space, optimizing models for real-time trading systems and contributing to cutting-edge generative AI advancements. The role offers substantial autonomy and resources, ideal for an innovative researcher eager to influence real-world applications in high-stakes environments.

Qualifications

• Experience in ML research or engineering, focusing on deep learning or generative models.
• Strong publication record in top-tier AI conferences like NeurIPS, ICML, or ICLR.
• Experience designing large-scale data annotation and curation pipelines.

Responsibilities

• Lead and contribute to research initiatives advancing LLM capabilities.
• Design and execute large-scale experiments from data pre-processing to model evaluation.
• Collaborate with engineers and traders to bring prototypes to production.

Skills

Machine Learning

Deep Learning

Python

Collaboration

Communication

Education

PhD in Computer Science, Machine Learning, or a related field

Tools

PyTorch

TensorFlow

JAX

Job description

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

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