absentia-labs · Boston
ABOUT ABSENTIA LABS Absentia Labs is building intelligent systems that sit at the intersection of AI, biology, chemistry, and large-scale engineering. Our goal is to translate complex scientific data into machine intelligence capable of reasoning, generalizing, and driving discovery. Biomedical data is fragmented, noisy, and deeply interconnected. Turning it into a useful signal requires not only strong data foundations but also carefully designed learning systems that can scale across modalities, tasks, and uncertainty regimes. This role focuses on building and training those systems. THE ROLE As a Senior AI/ML Engineer, you will lead the design, training, and deployment of large-scale machine learning models that form the core of Absentia Labs’ AI capabilities. You will work at the boundary between model architecture, training systems, and production infrastructure, with significant ownership over technical direction. This role is intended for engineers who have trained large models in real production environments, understand the realities of scale, and can reason about both learning dynamics and systems constraints. WHAT YOU’LL DO - Design, train, and evaluate large-scale models, including Large Language Models (LLMs), diffusion models, and Graph Neural Networks (GNNs). - Own end-to-end training pipelines, from dataset interfaces and batching strategies to distributed training and checkpointing. - Make principled decisions about model architecture, objective functions, optimization strategies, and scaling laws. - Build and optimize distributed training systems (data parallelism, model parallelism, sharding, mixed precision). - Collaborate closely with data engineers to define ML-ready datasets and streaming interfaces. - Translate ambiguous scientific or product requirements into robust ML solutions. - Drive model evaluation, ablation, and iteration with a focus on generalization, stability, and reproducibility. - Contribute to architectural decisions around mode…
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