- Silicon Valley, CA, United States
- Google Cloud
- Design, develop, test, deploy, maintain and improve data and ML pipelines.
- Work closely with data scientists to make improvements to models.
- Build pipeline to process billions of data points from petabytes of data.
- Manage project priorities, deadlines and deliverable.
- Proficient in Python.
- Expertise in working with at least one deep learning framework, such as PyTorch, Torch, TensorFlow, Caffe.
- Experienced in working with ETL pipelines.
- Strong analytical and problem solving skills.
- Versed in software engineering best practices (version control, code review process, etc.)
- Experienced in cloud providers such as GCP or AWS.
- Experienced in Software applications testing methodology, including writing and execution of test plans, debugging, and testing scripts and tools.
- A track record for delivering Machine Learning projects for a product.
- Excellent written and verbal communication skills.
- Strong and proactive communication, natural curiosity. Ambition to apply skills to a wide variety of fields
- Be able and open to pick up new skills, work with 3rd party technologies and devices.-
Today, most blood-based genetic tests are exploratory and typically followed by an intrusive
real diagnostic test. Our blood, however, is a treasure trove of information if handled properly. Truly diagnostic blood tests could dramatically change the way we manage our health personally and our healthcare as a society.
Recent advances in various areas of science and technology have created a possibility for truly diagnostic blood tests. Deepcell is developing a disruptive technology based on AI/ML, microfluidics and genetics that offers a non-invasive blood test with diagnostic-level accuracy.
In one word, we treasure cautious optimist attitude. Optimism alone may result in too much disappointment and too much caution does not get anything done.
- Google Cloud
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