Job Title: Real time Machine learning Engineer (RTML Engineer)
Location: Irving, TX or Basking Ridge, NJ or Tampa, FL or San Diago, VA
Duration: Long-term
Responsibilities:
- Functioning as a domain expert in the area of RTML model serving technology, familiar with the industrial trends in RTML, common RTML architectures, leading 3rd-party RTML serving products, and evaluation criteria's
- Working closely with other teams to define technical strategy, architecture, development choices and ensure overall growth of the Jarvis Framework to meet our internal customers needs.
- Leading the Jarvis development activities through phased releases, ensuring it is architecturally sound, implemented correctly/efficiently, and delivered on time.
- Supporting internal customers with major framework issues and coordinating triage efforts to solve them.
- Lead and mentor junior developers in the team and always pushing for team successes.
- Adhering to industry standards and best practices and tracking emerging RTML technologies and trends to continuously improve the Jarvis framework.
Skills Needed:
- Bachelor s degree or above in Computer Science/Engineering or other related areas.
- Four or more years of work experience in computer software development related jobs.
- At least two years are in AI / ML Engineering areas with reasonably good understanding of Data Science and AIML practices/workflows.
- Strong expertise in RTML model serving arena and/or large-scale cloud-based RT framework development.
- Experience with programming languages such as Python and Java.
- Experience in large application development in cloud environments- AWS, Google Cloud Platform and On-Prem clusters.
- Experience in K8s architecture and principle of operations, hands-on skills of deploying large applications in production K8s cluster, configuring K8s properly, and troubleshooting when the application has issues.
- Good understanding of RT system stats collection and performance monitoring methods.
- Basic understanding of RT Feature Engineering methodology and practices.
Even better if you have one or more of the following:
- Understand basic data science concepts and common needs from data scientists.
- Familiarity with common ML modeling frameworks such as TensorFlow and PyTorch.
- Experience with a scalable distributed model serving framework like Ray Serve will be very helpful.
- Strong collaboration skills and communication skills, especially when involving (non-tech) business stakeholders.
- Experience with cloud infrastructures and MLOps in clouds.
Familiar with CI/CD process and common frameworks such as ArgoCD