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Machine Learning Ops Technical Fellow - Permanent - $180k

  • Location:

    Austin

  • Sector:

    Informationstechnologie

  • Job type:

    Permanent

  • Salary:

    US$155000 - US$195000 per annum

  • Contact:

    Shannon Roberts

  • Contact email:

    Shannon.Roberts@oliverjames.com

  • Job ref:

    JOB-012023-194878_1675098993

  • Published:

    etwa 1 Jahr her

  • Expiry date:

    2023-03-01

  • Startdate:

    ASAP

Machine Learning Ops Technical Fellow - Permanent - Hybrid - $180k

**Hybrid Position: 1-3X in Office. Locations: Austin, TX OR Warren, Michigan**

This client is looking for a dynamic, experienced Machine Learning Ops (ML Ops) Technical Fellow to design and lead the vision of the ML Ops pipeline that will support Artificial Intelligence and Machine Learning (AI/ML) products and services. The Machine Learning Ops Technical Fellow will be responsible for driving technical direction and leadership for the development and operation of efficient ML pipelines that will support the business, research, and IT users in developing ML models. The focus will be driving external teams to implement service-based API architectures designed for the Mobile experience. This role will be responsible for help guide enterprise-wide strategic decision-making related to ML Ops.

Responsibilities:

  • Design, build, and maintain the core machine learning capabilities, services and platforms.
  • Lead teams and projects designing and deploying the company's ML Ops infrastructure.
  • Assist and guide teams deploying ML products and services and leveraging new ML tools.
  • Provide strategic vision and long-term planning for the company's ML Ops architectures and tooling to enable continuous capability expansion.
  • Implement components of ML-enabled applications at-scale in a distributed computing environment.
  • Drive testing, releases, and monitoring of machine learning based products on the platform.
  • Write high quality, shippable code across the stack that is easy to maintain and test.
  • Collaborate with ML scientists, machine learning engineers, and product teams to define high impact product features and deliver them with quality.
  • Scrutinize and clearly communicate the technology and architecture choices we make.
  • Implement integrated monitoring of model performance for reliability and maintenance.
  • Continuously improve ML processes, tools and standards.

Required Qualifications

  • 15+ years of software development and/ or architect-infrastructure engineering experience.
  • Proven track record and experience in orchestrating Machine Learning solutions to production at scale.
  • Proven track record of thought leadership. Experience of ML practice development in a large ML based product development organization is a plus
  • Should be able to handle multiple ML initiatives simultaneously and lead/mentor a team of
  • engineers
  • Applied background in machine learning platform development, software development, CI/CD and deployment patterns.
  • Experience with Data and ML Orchestration, Containerization, and GPU Compute technologies such as Docker, Spark, Kubernetes, and CUDA.
  • Experience with ML software technologies such as Pytorch, Tensorflow, Ray or sklearn.
  • Experience with workflow tracking and visualization technologies like ARGO, KubeFlow, MLFlow, TensorBoard, etc.
  • Strong Candidates will be knowledgeable in Data and ML Engineering with both on-prem and cloud infrastructure
  • Experience leading high-impact, cross-company initiatives
  • Excellent communication skills in presentation (both verbal and slides)

If this role is of interest, please contact Shannon today at shannon.roberts@oliverjames.com.

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