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Technical Services Engineer - Remote

Posted 4 weeks ago
Customer Service
Full Time
Worldwide

Overview

The Technical Services Engineer’s primary role is to serve as a technical advisor and champion for Anyscale customers, helping them onboard, adopt, and grow on Anyscale while troubleshooting and resolving customer tickets.

In Short

  • Be a solutions architect and technical advisor for key customers.
  • Own customer issues from troubleshooting to resolution.
  • Participate in a follow-the-sun customer support model.
  • Track customer bugs and feature requests.
  • Manage workload states of key customers.
  • Contribute to internal tools and documentation.
  • Provide feedback and collaborate with product and engineering teams.
  • Build relationships with technical stakeholders.

Requirements

  • 5+ years in a customer-facing technical role.
  • Experience in a fast-paced startup environment.
  • Hands-on experience in ML/AI, Data Engineering, and Data Science.
  • Knowledge of cloud platforms (AWS, GCP, Azure).
  • Excellent communication and interpersonal skills.
  • Strong sense of ownership and self-motivation.
  • Willingness to mentor and train peers.
  • Bonus: Experience with Ray and MLOps platforms.

Benefits

  • Market-based compensation.
  • Participation in equity and benefits offerings.
  • Stock options.
  • Healthcare plans with premiums covered at 99%.
  • 401k Retirement Plan.
  • Wellness and education stipends.
  • Paid parental leave.
  • Flexible time off.
  • Commute reimbursement.
  • 100% of in-office meals covered.
Anyscale logo

Anyscale

Anyscale is dedicated to democratizing distributed computing, making it accessible to software developers of all skill levels. The company is commercializing Ray, a widely-used open-source project that fosters an ecosystem of libraries for scalable machine learning. Major companies such as OpenAI, Uber, and Spotify utilize Ray to enhance their AI applications. Anyscale aims to provide the optimal environment for running Ray, enabling developers and data scientists to scale machine learning applications seamlessly from their laptops to clusters without needing extensive expertise in distributed systems. Backed by prominent investors like Andreessen Horowitz and NEA, Anyscale has raised over $250 million to date.

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