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Sr Machine Learning Engr - SSD (Durational 6mths to Hire)

Primary Location San Diego, California Job Number 1081625 Date posted 06/15/2022
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Description:
Job Summary:

Machine Learning Engineer will provide technical direction, execution and support of machine learning strategies for the SCPMG Medical informatics group. The position entails designing and implementing data pipelining, integration, and optimization of machine learning models to address healthcares triple aim: to improve the health of populations, to lower the cost of care, and to enhance the care experience.

Essential Responsibilities:


  • Use statistical and machine learning techniques to develop and improve clinical decision support tools

  • Design and develop data pipelines for machine learning applications

  • Optimize machine learning models to scale in real-time streaming applications

  • Integrate and deploy machine learning components in a production environment

  • Work closely with machine learning scientists, physicians, and other stakeholders

  • Lead small/sub-project efforts and provides visibility into team accomplishments to other departments/groups.

  • Reviews and provides practical feedback on group products and procedures.

  • Provides technical feedback on team members work.

  • Mentors team members acquiring new skills.

  • Seeks out open-source software packages or existing software code that can be reused or applied to assigned tasks.

  • Defines the logic, performs coding, tests, and debugs system components.

  • Develops and enforces current programming standards and change management.

  • Independently develop and modify testing components/scripts to support required functions.

  • Guide and help lower level developers in test-driven development (TDD) design/implementation.

  • Work with subject matter experts (SME) and senior developers to develop comprehensive testing plan/modules for self-developed software components.

  • Produces/archives process related artifacts such as design documents, test plans, wikis, and code review forms.

  • Deploys developed products to project environments.
Basic Qualifications:


Experience



  • Minimum six (6) years of programming or technical related experience.



Education



  • B.S. in Computer Science, Informatics, Physics, Mathematics, Engineering or related fields.



License, Certification, Registration



  • N/A



Additional Requirements:



  • Familiarity with Python and Java, expert in at least one of the two

  • Experience with pipelining, workflow, and orchestration tools such as Apache Airflow, MLFlow, Kubeflow

  • Experience with deep learning frameworks (e.g. Tensorflow)

  • Experience with SQL

  • Experience with source control tools for both code and models/data

  • Familiarity with classification and regression algorithms



Preferred Qualifications:



  • Demonstrated experience in Natural Language Processing

  • Demonstrated experience with machine learning integration and deployment in production environments

  • Demonstrated experience with Tensorflow Serving

  • Familiarity with C++/CUDA

  • Familiarity with healthcare terminology

  • M.S. in Computer Science, Informatics, Physics, Mathematics, Engineering or related fields.



 



Notes:




  • Durational position, 6 months to hire.

  • Retain all preferred qualifications.


Primary Location: California,San Diego,El Camino Real Administration Scheduled Weekly Hours: 40 Shift: Day Workdays: Mon, Tue, Wed, Thu, Fri Working Hours Start: 08:00 AM Working Hours End: 04:30 PM Job Schedule: Full-time Job Type: Standard Employee Status: Regular Employee Group/Union Affiliation: NUE-SCAL-01|NUE|Non Union Employee Job Level: Individual Contributor Department: Parsons West Annex - Prj Mgmt-Innovtn Proj-Qlty&Svc - 0806 Travel: Yes, 10 % of the Time Kaiser Permanente is an equal opportunity employer committed to a diverse and inclusive workforce. Applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy), age, sexual orientation, national origin, marital status, parental status, ancestry, disability, gender identity, veteran status, genetic information, other distinguishing characteristics of diversity and inclusion, or any other protected status.