LLM Researcher / Engineer

A world-class research organisation is seeking LLM Researchers and Engineers to join its interdisciplinary team in New York. This is a unique opportunity to contribute to cutting-edge large language model (LLM) development and apply advanced machine learning techniques to complex scientific challenges, including molecular science and drug discovery.

The team is known for pushing technical boundaries across AI, computational science, and specialised hardware. This role is ideal for individuals with deep expertise in LLMs and machine learning infrastructure who are eager to work on impactful, intellectually stimulating projects in a collaborative environment.

Your role as LLM Researcher or Engineer

This is a hands-on role contributing to both foundational research and applied development of LLMs for scientific domains. You'll collaborate with machine learning scientists, domain experts, and systems engineers to design and scale AI models and infrastructure.

Key responsibilities include:

• Developing large-scale training and inference pipelines using state-of-the-art compute infrastructure.

• Designing and optimising distributed training workflows for large language models.

• Contributing to pre-training (e.g. data pipeline design) and post-training efforts (e.g. reinforcement learning, contrastive learning, instruction tuning).

• Exploring multimodal learning strategies that integrate non-text modalities like molecular graphs, 3D structures, or time-series data.

• Advancing core research in LLM architecture, model scaling, and cross-domain adaptation.

• Collaborating across disciplines to explore novel applications of generative AI in scientific discovery.

Experience and qualifications for the LLM Researchers and Engineers role

Ideal candidates will bring a strong foundation in machine learning, deep learning systems, and large-model development, as well as a collaborative mindset.

Key qualifications include:

• Proven experience working with LLMs or large-scale ML systems in academic, research, or production settings.

• Strong proficiency in Python and ML frameworks (e.g. PyTorch, TensorFlow, JAX).

• Familiarity with distributed computing, parallel training strategies, and performance optimisation.

• Experience with or interest in post-training techniques such as RLHF, contrastive learning, or fine-tuning pipelines.

• Exposure to or curiosity about multimodal learning, especially involving scientific or structured data formats.

• A track record of innovation in machine learning, demonstrated through publications, contributions to open-source projects, or production-scale deployments.

• Intellectual curiosity, adaptability, and the ability to thrive in a cross-functional research environment.

Experience in molecular science or drug discovery is not required - what matters most is a strong technical foundation and willingness to engage with scientific applications.

Perks and benefits

• Work on meaningful AI research with direct impact on complex scientific challenges.

• Access to industry-leading infrastructure, including high-performance computing environments built for large-scale model training.

• Collaborate with a multidisciplinary team of world-class engineers, scientists, and ML experts.

• Hybrid working model: three days in-office (Tuesday-Thursday), two days remote (Monday and Friday).

• Competitive base salary range of $300,000-$800,000, plus sign-on and year-end bonuses.

• Comprehensive benefits package, including relocation and immigration support.

Apply now for immediate consideration.
If you're exploring roles at the intersection of LLMs, scientific research, and machine learning infrastructure, we'd welcome a conversation.