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Senior Machine Learning Engineer

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Description

At UPMC Enterprises, we use innovation and creativity to tackle exciting projects and develop cutting-edge technology to improve the lives of people all over the globe. Our daily work is nimble and entrepreneurial, cultivating new ideas to challenge the health care status quo. The office culture of UPMC Enterprises is also a reflection of this. In Bakery Square, you will find us in the heart of Pittsburgh’s Innovation Corridor. We have a casual dress code, flexible work hours, opportunities for professional development, as well as many employee-led efforts and activities.

 

 

Purpose:
At UPMC Enterprises, we help create health care innovations that will impact the lives of patients in meaningful, lasting ways. The Senior Machine Learning Engineer will perform both exploratory and targeted algorithm development and research to develop cutting-edge machine learning algorithms to help change the face of modern healthcare.

Responsibilities:

  • Communicate project activities, statuses, accomplishments, and strategic direction with executive management both in oral and written communication
  • Communicate the results and methodology effectively within the team and to external stakeholders
  • Define and lead the development of long-term machine learning platforms and data systems Innovate in the space of machine learning algorithms 
  • Evaluate new hardware and software products and technologies and participate in project assessments as necessary
  • Implement and evaluate proposed model/methodology
  • Implementing Packaged Solutions: Configuration & Testing: In-depth knowledge of a particular Packaged Solution and of the business processes the package supports. Customize the package for local needs using propriety APIs, tools, and scripting languages. Develop and validate system requirements and specifications. Design schemes, architecture and models and create and test prototypes. Develop, or acquire and customize and test system/application components and interfaces. Integrate subsystems/application units and conduct systems/applications level testing and validation. Develop and implement system/application release and testing.
  • Promote and participate in professional self-development to stay up-to-date with new technologies and development approaches within the industry
  • Propose statistical or machine learning based model/methodology for problem-solving 
  • Propose accuracy measures and validation criteria for the model
  • Provide guidance on reporting, analyses, model/methodology for delivery of improvement strategies to fast-paced machine learning development projects
  • Work with product managers, partners and peers to formulate the data analytics problem

 

Qualifications


  • Bachelor's degree in Computer Science, Applied Math, Statistics, Operations Research, Physics, Computational Biology or other similar quantitative field (MS or PhD preferred) or has acquired substantial software development and machine learning skills and knowledge via practical experience 5+ years of relevant experience (machine learning and software engineering
  • Demonstrated expertise in statistical analytics and machine learning algorithms especially for supervised and unsupervised methods
  • Expert knowledge in essential high level programming language like Java, Python, C++, Ruby
  • Proficiency in at least one statistical modeling tool from among R, Matlab or Weka Experience with Hadoop/YARN/Mesos/Spark/Elasticsearch/Kafka and building applications end-to-end
  • Prefer experience in data science, data manipulation, data wrangling, data munging
  • Experience processing and interpreting large volumes of data in various forms preferred
  • Some healthcare or biomedical domain knowledge a plus

    Licensure, Certifications, and Clearances:
    UPMC is an equal opportunity employer. Minority/Females/Veterans/Individuals with Disabilities

 

Location: Pittsburgh, PA, United States
Job ID: 773996

UPMC is an equal opportunity employer.
Minority / Females / Veterans / Individuals with Disabilities