Senior Machine Learning Engineer

NO C/C

ONLY W2

Must be local for the hybrid schedule

--------------------------------Please no Third Party Vendors--------------------------------------------

Senior Machine Learning Engineer (ML Ops / Deep Learning)

Mountain View, CA (Hybrid – 3 days onsite)

Contract (4–5 months)

Start: ASAP

About the Role

We are looking for a Senior Machine Learning Engineer to join a high-impact team working on advanced data products related to seismic and well log data. This role focuses on identifying geologic features (e.g., faults, horizons) using cutting-edge ML techniques.

You will work on large-scale model training, image and signal processing, and ML pipeline development in a highly collaborative environment.

Key Responsibilities

• Design, build, and deploy machine learning models for image and time-series (sensor) data
• Develop and optimize deep learning models (training & inference on GPUs)
• Build and maintain scalable ML pipelines (Vertex AI, Kubeflow, etc.)
• Work with large datasets (image, seismic, and subsurface data)
• Implement ML Ops best practices (monitoring, versioning, deployment)
• Collaborate with cross-functional teams to prototype and validate solutions

Required Skills

• Strong experience with deep learning (image models, GPU training & inference)
• Hands-on experience with ML Ops frameworks and distributed training pipelines
• Experience with TensorFlow and/or PyTorch
• Solid experience with GCP (Google Cloud Platform)
• Experience building data pipelines for image or sensor data
• Experience with model training, fine-tuning, and deployment
• Familiarity with data labeling tools
• Strong communication and problem-solving skills

Nice to Have

• Experience with Vertex AI, Kubeflow
• Knowledge of subsurface / seismic / geologic data
• Experience with Protocol Buffers and containerization
• Experience with edge deployments
• Strong prototyping mindset (ability to quickly validate hypotheses)