Why This Role Stands Out
This hybrid Senior Machine Learning Engineer role offers a fantastic opportunity to leverage your expertise in computer vision and deep learning to tackle complex seismic and well log data challenges at a reputable technology firm. You'll thrive if you're passionate about building and deploying cutting-edge ML models, with ample room for growth and skill development in MLOps and cloud technologies. Apply now to contribute to innovative solutions and enjoy the flexibility of a hybrid work environment.
Quick Overview
Job Description
Position: Senior Machine Learning Engineer
Location: Mountain View, CA (Hybrid or Remote)
Duration: 12+ Months
Key skills: ML Ops, computer vision (image models and processing), deep learning, GPU training, Google Cloud Platform, TensorFlow, PyTorch, Agentic coding tools
Role Overview:
We are looking for an ML Engineer who will be working on products related to seismic and well log data, identifying simple geologic characteristics of the data (faults, horizons). Full stack ML with the focus on signal processing - image and time series.
We are looking for a candidate who:
- Versed in deep learning, GPU training and inference, image models.
- Seasoned in model training and setting distributed model training pipelines. Specifically using Vertex, Kubeflow, etc for training of larger models on large amounts of data (Image, language).
Requirements:
- Strong experience in building and deploying machine learning models, with a focus on image processing and time series signal processing.
- Experience in training and fine-tuning ML models.
- Experience in building and maintaining data pipelines for image and other sensor data.
- Experience with ML Ops tools and practices, such as model monitoring, versioning, and deployment.
- Experience in working with data labeling tools.
- Experience with cloud platforms, Google Cloud Platform in particular. Experience with edge deployments is a plus
- Excellent communication and collaboration skills.
- Ability to work independently and as part of a team.
- Strong problem-solving skills.
- Passionate about machine learning and its applications.
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