Machine Learning Engineer
Location: Pittsburgh, PA
Job Type: Contract
We are growing and the data processing landscape is shifting. We collect terabytes of data of various types, including real-time, from a cadre of sources from all of our clients. Our clients, large and small health systems, too are growing. The kinds and amount of data that each generates on a yearly basis is exponentially growing. Having this data improves our clients’ situational awareness leading them to better understand how they are performing in order to improve their overall outcomes. This is true for the smallest community hospital to the largest health system.
As a Machine Learning Engineer you will be working in one of the most complex data environments in healthcare. You will be responsible to determine ways to intelligently use this data to enhance the users’ experience and to inform customers of trends identified by the data. You should have excellent business and communications skills to be able to work with both technical teams as well non-technical teams and direct with our clients. You should be someone who loves to bring data together to answer business questions and drive change.
- Create machine learning models and applications. Use your strong multiple programming languages to lead the design and development of the next generation machine learning algorithms that will drive operational improvements across the healthcare continuum of careand dramatically improve insights for all our stakeholders both internal (analysts, business leaders, etc.) and external (clinicians, health system CEOs and CIOs, etc,).
- Select appropriate databases and data representation methods that ensure successful testing of machine learning models and are representative of our client’s data.
- Perform statistical analysis and fine-tuning using test results.
- Run machine learning tests and experiments.
- Keep abreast of developments in machine learning and statistics.
Education & Experience:
- Bachelors in Computer Science, Machine Learning or related field
- Masters preferred
- 8 Years of total software engineer experience of which 4+ years of experience building functional ML applications for prediction, utilization (e.g., commercial products or government projects), NLP
- Previous experience in using Hadoop ecosystem ML tools (SparkML, Mahout, etc.)
- Experience validating software through industry accepted testing strategies
- Experience working in an Agile development environment
- Proven experiences on delivering distributed systems and services in a production setting
- A portfolio of relevant publications or open-source projects to share with us
- A desire to keep up with the field by attending or publishing at relevant conferences (ACL, EMNLP, NAACL-HLT, ICML, NIPS, etc.
- Graduate-level expertise (or equivalent industry experience) in machine learning, natural language processing, or related field
- Expert knowledge in implementing ML systems at scale in Python, Java, Scala, SparkML, or C/C++ (i.e., not just R or MATLAB)
- Be responsible for the architecture, design, development, and operations of large-scale systems designed for machine learning. These may include, but not limited to, data management systems, data engineering workflow systems, distributed compute systems, and their web portal & web service components
- A strong mathematical background in statistics and machine learning. Understands datastructures, data modeling, and software architecture.
- Great presentation and communication skills
- Experience with some or all of the following:
- REST API’s
- Amazon Web Services
- Windows and Linux