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Sr Data Scientist/Machine learning software engineer

Vortexlink MOFFETT FIELD Full-Time
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Sr Data Scientist/Machine learning software engineer

This position (Full Time) is based in Mountain View, CA, reporting to the CTO.

Responsibilities

  Design and develop machine learning models to solve specific problems in the healthcare/medical domain. Perform feature engineering, apply the latest published research, and tune model hyperparameters to achieve high model performance.

 Train models on large volumes of data across many different kinds of sensor signals.

Work with platform software engineers to deploy the ML models to Production and integrate them into customer-facing features on the Twins platform.

 Measure model performance and continuously improve over time.

Qualifications

 Bachelor’s degree in Computer Science, Math, or Statistics; Masters or PhD would be a plus

 Experience with building Production-quality ML models to solve real-world problems, using techniques like Deep Neural Networks, Gradient Boosting, etc. ○ Experience with TensorFlow, scikit-learn, or related technologies. ○ Experience developing software in Python; experience in other languages like Java would be a plus.

 Strongly desired: ○ Experience with sequence learning, including Recurrent Neural Networks, LSTM, Attention Networks, etc. ○ Experience with pattern recognition and anomaly detection.

 2+ years of experience in machine learning; 4+ years in overall software engineering is preferred

 Strong knowledge of linear algebra, calculus, statistics

 Strong verbal communication skills; able to translate ML technology and statistics to non-ML experts

 Domain experience in healthcare, biosensors, or related areas would be a plus, but is not required

Sr Data Scientist/Machine learning software engineer

This position (Full Time) is based in Mountain View, CA, reporting to the CTO.

Responsibilities

  Design and develop machine learning models to solve specific problems in the healthcare/medical domain. Perform feature engineering, apply the latest published research, and tune model hyperparameters to achieve high model performance.

 Train models on large volumes of data across many different kinds of sensor signals.

Work with platform software engineers to deploy the ML models to Production and integrate them into customer-facing features on the Twins platform.

 Measure model performance and continuously improve over time.

Qualifications

 Bachelor’s degree in Computer Science, Math, or Statistics; Masters or PhD would be a plus

 Experience with building Production-quality ML models to solve real-world problems, using techniques like Deep Neural Networks, Gradient Boosting, etc. ○ Experience with TensorFlow, scikit-learn, or related technologies. ○ Experience developing software in Python; experience in other languages like Java would be a plus.

 Strongly desired: ○ Experience with sequence learning, including Recurrent Neural Networks, LSTM, Attention Networks, etc. ○ Experience with pattern recognition and anomaly detection.

 2+ years of experience in machine learning; 4+ years in overall software engineering is preferred

 Strong knowledge of linear algebra, calculus, statistics

 Strong verbal communication skills; able to translate ML technology and statistics to non-ML experts

 Domain experience in healthcare, biosensors, or related areas would be a plus, but is not required

Recommended skills

Recurrent Neural Networks
Feature Engineering
Scikit Learn
Deep Learning
Tensorflow
Linear Algebra
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