Staff Machine Learning Operations Engineer

Position Summary:

The Staff Machine Learning Operations Engineer is recognized as a master in Machine Learning Operations and is responsible for the design, development, analysis, testing, and implementation of Machine Learning (ML) services and infrastructure. The candidate will test new technologies, develop best practices and guides, and serve as a subject matter expert for the Development Operations & Analytics Team. This Staff-level position works on significant and unique issues where analysis of situations and data requires an evaluation of intangibles. They communicate project information to clients, project managers, or other design personnel working on projects, maintaining good working relationships with clients and staff. They write and maintain complete documentation, support team members, and ensure established goals and deadlines are met. They keep management informed of status and significant problems.

Job Details:

Work from Home
Monday to Friday | 9 AM to 6 PM MST (12 AM to 9 AM Philippine Time)

Responsibilities:

• Design and develop web/backend and CI/CD services.
• Manage multiple tasks and responsibilities in high-pressure environments, excelling at pinpointing and resolving problems in early project stages to avoid cost/time expenses.
• Deliver high-quality projects on time through the ability to design architecture.
• Write high-quality code and effective unit tests, establishing and enforcing standards for other engineers.
• Monitor and optimize performance for high-utilization 24x7 services.
• Reduce incident occurrence by eliminating root causes and continually improving and advocating for organizational best practices and standards.
• Research and integrate third-party products with existing infrastructure.
• Anticipate the future state of the ML Ops platform and continuously update architecture.
• Evaluate technology over mid to long-term time horizons and consider business and technical trade-offs.
• Work with product teams to gather business processes and project requirements.
• Research, design, and develop computer software systems in conjunction with hardware product development, applying principles and techniques of computer science, engineering, and mathematical analysis.
• Analyze software requirements to determine feasibility of design within time and cost constraints.
• Consult with hardware engineers and other engineering staff to evaluate and recommend interface between hardware and software, and operational and performance requirements of overall systems.
• Formulate and design complex software systems, using scientific analysis and mathematical models to predict and measure outcomes and consequences of design.
• Develop and direct software system testing procedures, programming, and documentation.
• Ensure the work area is clean, secure, and well maintained.
• Perform miscellaneous projects as assigned.
• Update technical skills as required.
• Perform other related duties as assigned.

Knowledge, Skills, and Abilities:

• Experience with operating high-availability, fault-tolerant, scalable, distributed software/infrastructure in production utilizing DevOps best practices.
• Excellent understanding of issue troubleshooting and performance tuning.
• Commitment to quality through the ability to translate complex technical requirements into functional software using best practices to write high-quality code.
• Ability to work in a self-managed team-based Agile project environment, providing technical guidance and leadership to other team members.
• Excellent experience with software engineering standard methodologies (unit testing, code reviews, design documentation, continuous delivery).
• Develop and deploy production-grade services, SDKs, and data infrastructure emphasizing performance, scalability, and self-service.
• Excellent experience with existing MLOps frameworks (e.g., Databricks, Seldon, SageMaker, DVC).
• Strong background with either Scala (Java), Go, or Python programming experience.
• Solid experience operating big data infrastructure in a cloud-based ecosystem (AWS preferred).
• Solid understanding of traffic management and networking concepts.
• Experience with stream-processing systems (e.g., ksqlDB, Spark Streaming, Apache Beam/Flink).

Qualifications:

• Bachelor of Science Degree in Computer Science, Information Technology, or a related field.
• Subject matter expert in area of responsibility or extensive knowledge of several technical areas.
• Advanced degrees (Master’s or PhD) may reduce the experience requirement by 2-4 years.
• Minimum of 6 years' experience with a proven track record in developing web-based applications and web services using Java, SOAP, REST, XML, and other web technologies, including experience interfacing with Oracle databases and integrating third-party products with existing infrastructure.

Preferred Qualifications:

• Experience with:
  • NetBeans
  • Subversion
  • Jira
  • Agile/Scrum project development
  • IDM/OSSO
  • ASP/.Net
  • DRUPAL
  • Groovy/Grails
  • Ruby/Rails
  • PHP
  • Hibernate/Seam
  • Banner
  • DROOLS, JBOSS
  • Technical Certification
  • Application Integration with legacy systems
  • JSF, J2EE, Java EE, jQuery, JavaScript
  • SQL
  • Oracle or another database interface