Senior ML Systems Engineer - Large-Scale AI (Remote/Hybrid)

Absentia; Northern (KY); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Equity

Foundational ML systems

Autonomy

Flexible work

Job summary

Absentia Labs seeks a Senior AI/ML Engineer to lead design, training, and deployment of large-scale models at scale. You will own end-to-end training pipelines and collaborate across data, infra, and product teams.

You bring 5+ years in ML or applied AI, hands-on with LLMs/diffusion/GNNs, and strong PyTorch skills, with a track record of production-grade systems and scalable training architectures.

Qualifications

• 5+ years in ML or applied AI
• Experience training large-scale models in production
• Hands-on with LLMs, diffusion models, and/or GNNs
• Strong PyTorch or equivalent frameworks
• Distributed training and scaling knowledge
• Experience with large datasets and high-throughput pipelines
• Strong SDLC skills: tests, reproducibility, debugging

Responsibilities

• Design, train, and evaluate large-scale models (LLMs, diffusion, GNNs).
• Own end-to-end training pipelines, including data interfaces, batching, and distributed training.
• Decide on architectures, objectives, optimization, and scaling laws.
• Build and optimize distributed training systems (data/model parallelism, sharding, mixed precision).
• Collaborate with data engineers to define ML-ready datasets and streaming interfaces.
• Translate scientific or product requirements into robust ML solutions.
• Drive model evaluation, ablation, and iteration for generalization and stability.
• Contribute to model serving, inference efficiency, and lifecycle decisions.
• Provide technical leadership through reviews and cross-team collaboration.

Skills

5+ years experience

Production ML

LLMs

Diffusion Models

GNNs

PyTorch

Distributed Training

Data Pipelines

Software Engineering

Communication

Tools

PyTorch

Job description

Absentia Labs seeks a Senior AI/ML Engineer to lead design, training, and deployment of large-scale models at scale. You will own end-to-end training pipelines and collaborate across data, infra, and product teams.

You bring 5+ years in ML or applied AI, hands-on with LLMs/diffusion/GNNs, and strong PyTorch skills, with a track record of production-grade systems and scalable training architectures.