Software Engineer - ML Infrastructure
Epsilon Labs, Inc.about 2 hours ago
Responsibilities
- Build and optimize distributed training infrastructure for medical imaging models.
- Develop reinforcement learning training stack for online, multi-reward RL.
- Create high-throughput data loading and preprocessing for large datasets.
- Design robust data pipelines for processing multimodal medical imaging data.
- Implement centralized data storage solutions for efficient data retrieval.
- Collaborate with researchers to prototype and deploy new ideas.
- Contribute to production serving and deployment pipelines.
Requirements
- 5+ years of experience in building ML infrastructure or data pipelines in production.
- Strong Python skills and expertise in PyTorch or JAX.
- Experience with distributed training at scale and efficiency concerns.
- Hands-on experience with data pipeline technologies like Spark or Airflow.
- Familiarity with cloud infrastructure (AWS/GCP) and containerization (Docker/Kubernetes).
- Proven track record of building scalable data systems and shipping ML infrastructure.
- Ability to manage competing priorities in a fast-paced environment.
Tech Stack
Apache AirflowApache SparkAWSDatabricksDockerGoogle BigQueryGoogle Cloud PlatformKubernetesPythonPyTorchSnowflake