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)