Description

You will lead small engineering teams while remaining hands-on, building and deploying ML models for seismic and well log data analysis.

This role is hybrid.

Responsibilities

• Identify geologic characteristics such as faults and horizons in subsurface data.
• Build and maintain data pipelines for image and sensor data.
• Set up distributed model training pipelines using Vertex AI and Kubeflow.
• Train, fine-tune, and deploy image and time-series signal processing models.
• Implement MLOps practices including model monitoring, versioning, and deployment.

Required Skills

• 10+ years of experience in software or ML engineering.
• Deep expertise in Deep Learning, GPU training, and inference.
• Proficiency with TensorFlow and PyTorch frameworks.
• Extensive experience with Google Cloud Platform (GCP).
• Hands-on experience with Agentic coding tools (e.g., Claude).
• Strong background in image models and time-series signal processing.
• Experience setting up distributed training pipelines on Vertex AI or Kubeflow.
• Familiarity with data labeling tools and containerization technologies.

Preferred Skills

• Experience with Protocol Buffers.
• Knowledge of edge deployments.

Key Skills

Education

Any Graduate