Absentia Labs

United States
7 Total Employees
Year Founded: 2024

Jobs at Absentia Labs

Let Your Resume Do The Work
Upload your resume to be matched with jobs you're a great fit for.

Recently posted jobs

17 Hours AgoSaved
Hybrid
Boston, MA, USA
Artificial Intelligence • Machine Learning • Biotech • Pharmaceutical
Conduct independent AI research for predictive toxicology and drug safety. Develop novel deep learning architectures, multimodal models, representations, uncertainty methods, and mechanistic reasoning approaches for heterogeneous biological and chemical data. Design rigorous experiments, benchmarks, ablations, and generalization evaluations while collaborating with engineering and scientific teams to translate validated research into scalable modeling systems. Contribute to scientific strategy, publications, collaborations, and regulatory validation.
19 Hours AgoSaved
Hybrid
6 Locations
Artificial Intelligence • Machine Learning • Biotech • Pharmaceutical
Lead the design, training, evaluation, and deployment of large-scale machine learning models, including LLMs, diffusion models, and GNNs. Own distributed training pipelines, dataset interfaces, optimization strategies, model evaluation, serving, and lifecycle management. Collaborate with data, infrastructure, and scientific teams while providing technical leadership through architecture reviews, mentorship, and cross-functional decision-making.
21 Days AgoSaved
Hybrid
Boston, MA, USA
Artificial Intelligence • Machine Learning • Biotech • Pharmaceutical
Lead design, training, and deployment of large-scale ML models (LLMs, diffusion, GNNs). Own end-to-end training pipelines, distributed training, and evaluation. Collaborate with data and infra teams, drive architecture and inference decisions, and provide technical leadership and mentorship.
One Month AgoSaved
In-Office or Remote
6 Locations
Artificial Intelligence • Machine Learning • Biotech • Pharmaceutical
Lead design, training, and deployment of large-scale ML models (LLMs, diffusion, GNNs). Own end-to-end training pipelines, distributed training, evaluation, and inference architecture. Collaborate with data and infra teams, drive reproducible model development, and provide technical leadership and mentorship from research through production.