Senior AI / Machine Learning Engineer

You are a senior ML engineer who thinks holistically about models as systems. You are comfortable operating under uncertainty, making trade-offs between compute, data, and performance, and owning outcomes from research through production.

You care deeply about training dynamics, failure modes, and scaling behavior, and you have the scars to prove it.

5+ years of industry experience in machine learning or applied AI roles.

Demonstrated experience training large-scale models in production settings, not just prototypes.

Hands-on expertise with LLMs, diffusion models, and/or GNNs.

Strong proficiency in PyTorch (or equivalent deep learning frameworks).

Deep understanding of distributed training, including parallelism strategies and performance optimization.

Experience working with large datasets and high-throughput data pipelines.

Strong software engineering fundamentals: clean code, testing, reproducibility, and debugging at scale.

Ability to clearly communicate technical trade-offs to both technical and non-technical stakeholders.

Experience with reinforcement learning, fine-tuning, or preference-based optimization (e.g., RLHF).

Familiarity with model compression, distillation, or inference optimization.

Experience deploying models in production inference systems.

Exposure to multimodal learning or foundation models.

Prior work in startups or fast-moving R&D environments.

Contributions to open-source ML frameworks or research codebases.

Note: Prior experience with molecular or biomedical models is not required . We value strong ML systems experience and the ability to transfer learning across domains.

Absentia Labs is an equal opportunity employer. We believe diverse teams build better systems and stronger science, and we encourage applicants from all backgrounds to apply.