Senior Software Engineer - Machine Learning
- Expired: over a month ago. Applications are no longer accepted.
As the Senior Software Engineer (Machine Learning) you will:
- Provide expertise and direction in the development and/or modification of computer-based scientific, technical, and business software systems.
- Use your expertise to design develop, code, test, and debug software.
- Work in one or several areas, such as equipment or software design, engineering evaluation or test, configuration management procedures, statistical analysis, and modeling.
- Work with users to define existing or new system scope and objectives.
- Provide analytical support and technical advice during the conceptualization, development, and implementation phases.
- Plan and schedule new applications systems projects with user, systems software, and computer center operations personnel, including the identification of objectives, time frames, costs, and manpower requirements.
- Perform tasks necessary to ensure the identification and documentation of hazards within software systems using various analysis tools and techniques.
- Review and evaluate systems and software for adherence to the government or commercial directives, standards, guidelines, and criteria concerning software safety and systems safety.
- Confirm design mitigations are captured in the design and its documentation and verify implementation.
- Potentially perform as a project lead with the responsibility for the instruction, assigning, direction, and monitoring of the performance of assigned systems developers/analysts working on a specific project.
- Degree in Computer Science or a related form of engineering training.
- 12+ years of relevant work experience in Software Engineering including demonstrated experience with Machine Learning tools and technology.
- A Security Plus certification is required.
- Experience with cloud computing infrastructure (e.g. Amazon Web Services EC2, Elastic MapReduce, Kubernetes) and considerations for scalable, distributed systems.
- Experience with high-scale or distributed RDBMS is a plus.
- Experience with industry-standard medical data models, e.g. HL7, OMOP, ICD 9/10, a plus.
- Experience using Kubernetes (Docker).
- Build and deploy environments using Kubernetes (Docker).
- Design and build an automated system for hypothesis generation and testbeds that can operate various services and handle user traffic. Build a Kubernetes cluster to allow developers to create and update infrastructure components at any time, allowing easy service expansion.
- Build a robust monitoring system to easily check the status of services and detect system anomalies immediately.
- Anticipate and respond to system anomalies in advance.
- Immediately identify and act through the log infrastructure and analytics system.
- Experience with Amazon Web Services, Azure, and/or Google Cloud Platform.
- Experience with container technologies and orchestration (Kubernetes).
- Experience with source control, Continuous Integration, and Test-Driven Development methods (Git, Selenium, Jenkins).
- Candidates must have demonstrated experience in troubleshooting problems and working with a team to resolve web-scale production issues.
- Familiarity with Scikit Learn, Numpy, Pandas, Pytorch, Tensorflow, Keras, SDLC (Software Development Lifecycle), and Microservice Unit test framework Pytest.
- Collaborating with AI Scientists to understand the crux of Model Development and serve it in a production environment.
- Must be able to obtain a Public Trust clearance.
Established in 2010, @Orchard LLC, also known as, Talent Orchard has an exceptional reputation, providing staffing solutions to time-sensitive, talent scarcity issues to deliver better talent management ROI. Our specialty lies in the critical area of program talent acquisition and resource management, not in one narrow skillset, but across many areas of technical and functional delivery. To learn more about our other exciting opportunities, visit our Jobs Page at www.atOrchard.com.
TechnologyView all jobs at @Orchard