Job description

Job Description


  • 2+ years of experience with Machine Learning Technologies.
  • 2+ years of work experience as a software engineer with exceptional software engineering knowledge.
  • Experience and good understanding of Machine Learning / Deep Learning Models / Python / Natural Language Processing
  • Understanding or desire to learn end to end Machine Learning technology stack (Tools such as Kubeflow, Kubernetes, OpenShift, SeldonCore, GCP, Jupyter Notebook, HPC, Hive, Hadoop, etc).
  • Strong soft skills of communication, ability to share/teach others, work collaboratively with others etc.


Responsibilities


  • Work closely with Tech Anchor, Product Manager and Product Owner to deliver machine learning use cases using Ford Agile Framework.
  • Work with Software and ML engineers to tackle challenging AI problems.
  • Work specifically on the Deploy team to drive model deployment and AI/ML adoption with other internal and external systems.
  • Help innovate by researching state-of-the-art deployment tools and share knowledge with the team.
  • Lead by example in use of Paired Programming for cross training/upskilling, problem solving, and speed to delivery.
  • Leverage latest GCP, CICD, ML technologies


Qualifications


  • A Bachelor’s degree in Computer Science / Computer Engineering or similar technical discipline.
  • 2+ years of experience with Machine Learning Technologies.
  • 2+ years of work experience as a software engineer with exceptional software engineering knowledge.
  • Experience and good understanding of Machine Learning / Deep Learning Models / Python / Natural Language Processing
  • Understanding or desire to learn end to end Machine Learning technology stack (Tools such as Kubeflow, Kubernetes, OpenShift, SeldonCore, GCP, Jupyter Notebook, HPC, Hive, Hadoop, etc).
  • Strong soft skills of communication, ability to share/teach others, work collaboratively with others etc.
  • Good understanding of cloud design considerations and limitations and impact of pricing.
  • Proficient in Python, and ML, Deep Learning frameworks/libraries.
  • Prior experience working with container technology, docker files, docker images, GitHub, CI/CD concepts.

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