About the job
About Absentia Labs
Absentia Labs is at the forefront of innovation, creating intelligent systems that integrate artificial intelligence, biology, chemistry, and large-scale engineering. Our mission is to convert intricate scientific data into machine intelligence that can reason, generalize, and foster discovery.
We tackle the challenges of fragmented, noisy, and interconnected biomedical data, transforming it into a meaningful signal through robust data foundations and well-designed learning systems that are scalable across different modalities, tasks, and uncertainties. This position emphasizes the design and training of such systems.
The Role
As a Senior AI/ML Engineer, you will spearhead the architecture, training, and deployment of large-scale machine learning models that are central to Absentia Labs’ AI initiatives. Your role will bridge model architecture, training systems, and production infrastructure, granting you significant ownership of the technical direction.
This position is tailored for engineers experienced in training large models in real-world production settings, who are adept at navigating scale and can analyze both learning dynamics and system 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 informed decisions regarding model architecture, objective functions, optimization strategies, and scaling principles.
- Develop and enhance distributed training systems (data parallelism, model parallelism, sharding, mixed precision).
- Collaborate closely with data engineers to establish ML-ready datasets and streaming interfaces.
- Translate vague scientific or product requirements into solid ML solutions.
- Lead model assessment, ablation, and iteration with a focus on generalization, stability, and reproducibility.
- Contribute to architectural decisions concerning model serving, inference efficiency, and lifecycle management.
- Provide technical leadership through design reviews, mentorship, and cross-functional collaboration.
Who You Are
You are a senior ML engineer with a holistic approach to models as systems. You comfortably navigate uncertainty, make informed trade-offs between compute, data, and performance, and take ownership of outcomes from research through to deployment.
