Machine Learning Researchers (LLM) Scientist, Sr. Scientist, Principal Scientist

Unclassified - Cambridge, MA

Full-time - Mid Level

Cambridge, MA

About the position

FL97 is seeking experienced, creative, and talented Machine Learning Researchers (LLMs) across Scientist, Senior Scientist, and Principal Scientist levels to join our team. The title will be determined by merit and experience level. You will be part of an agile, cross-functional team responsible for training state-of-the-art, large-scale models on the scientific corpora, fine-tuning models with feedback (e.g. RLHF/DPO), and integrating multimodal scientific data. Together with biologists, bioinformaticians, software developers, and automation engineers, you will work on reimagining the way scientific research is conducted. The ideal candidate has a machine learning background, with previous experience building large-scale generative models, complex pre-processing pipelines, and comprehensive benchmarks to support scientific tasks. Mature software engineering skills and familiarity with best practices in software development are also highly desired. Candidates should have experience and/or interest in designing, training, and fine-tuning large language models (LLMs), including the ability to successfully adapt an LLM for use in a specific domain. Leveraging NLP tools to solve real-world problems that require sequential decision making is also crucial. Implementing rigorous testing, documentation, and model benchmarking will be part of your responsibilities.

Responsibilities

• Train state-of-the-art, large-scale models on scientific corpora.
• Fine-tune models with feedback (e.g. RLHF/DPO).
• Integrate multimodal scientific data into models.
• Collaborate with biologists, bioinformaticians, software developers, and automation engineers.
• Design, train, and fine-tune large language models (LLMs).
• Leverage NLP tools to solve real-world problems requiring sequential decision making.
• Implement rigorous testing, documentation, and model benchmarking.

Requirements

• PhD in computer science, applied mathematics, physics, computational biology, or other quantitative disciplines.
• 5+ years of experience in developing deep learning and/or NLP models.
• Contributions to research conferences or journals (e.g. NeurIPS, ICML, AAAI, ICLR).
• Expertise in at least one ML framework (PyTorch/TensorFlow/Jax).
• Robust experience in the Python data science ecosystem.
• Experience in training and deploying ML models on distributed computing services (e.g. AWS/GCP/Azure, or clusters).

Nice-to-haves

• Experience with knowledge graphs, prompting techniques (e.g., Chain-of-Thought), RAG, and/or autonomous agents.
• Incorporating models into AI-enabled toolchains for the biology lab.

Benefits

• Access to advanced technology in AI experimental design and simulation.
• Access to automated liquid handling and instrumentation.
• Access to generative molecular design.