Machine Learning Engineer

About the role

Artera is developing AI-driven medical tests to tailor cancer therapies. As a Machine Learning Engineer, you will contribute to our AI Platform by building efficient systems for training, evaluating, and processing models and data. You will collaborate with AI developers and platform engineers to ensure our model developers have reliable, high-performance training and deployment capabilities.

Key facts

What you'll do

• Develop and manage the ML compute infrastructure, including systems for scaling foundation model development through distributed training and custom libraries.
• Create and improve the foundational software used by AI scientists for developing, deploying, and monitoring AI products.
• Partner with model developers to enhance the efficiency of GPU and CPU usage, as well as data flow for large-scale foundation models and subsequent training.
• Improve Artera's capacity to store and efficiently serve terabytes of digital pathology data for large-scale training initiatives.
• Ensure our monitoring systems provide clear insights for continuous performance optimization across all models.

Requirements

• A minimum of 5 years in professional software engineering.
• At least 4 years of professional experience using PyTorch, TensorFlow, or JAX with Python.
• A minimum of 3 years of professional experience with AWS, Docker, and Kubernetes.
• At least 1 year of professional experience optimizing large-scale, high-throughput, distributed machine learning training pipelines.

Nice to have

• Experience with ML orchestration tools such as Flyte, Ray, Kubeflow, Metaflow, MLFlow, Dagster, Argo Workflow, or Prefect.
• Familiarity with Terraform and SqlAlchemy.
• Experience with multi-node and multi-GPU training.
• Experience deploying and maintaining infrastructure for both ML training and production inference.
• Knowledge of inference optimization techniques like TorchScript, ONNXRuntime, DeepSpeed, or AWS Neuron.

Skills & tools

• Python
• PyTorch, TensorFlow, or JAX
• AWS
• Docker
• Kubernetes
• Distributed Systems

Practical notes

• This role is remote and open to individuals authorized to work in the United States or Canada without requiring future employment-based visa sponsorship. Artera does not sponsor visas for this position.
• Eligible candidates include those with permanent work authorization in the US (e.g., citizens, permanent residents) or those authorized to work in Canada (e.g., citizens, permanent residents).
• Visa transfers are not supported for this role.