Platform engineer, MLOps

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About This Role
As a Platform engineer, MLOps, you will be critical to deploying and managing cutting-edge infrastructure crucial for AI/ML operations, and you will collaborate with AI/ML engineers and researchers to develop a robust CI/CD pipeline that supports safe and reproducible experiments. Your expertise will also extend to setting up and maintaining monitoring, logging, and alerting systems to oversee extensive training runs and client-facing APIs. You will ensure that training environments are optimally available and efficiently managed across multiple clusters, enhancing our containerization and orchestration systems with advanced tools like Docker and Kubernetes.

About This Role
As a Platform engineer, MLOps, you will be critical to deploying and managing cutting-edge infrastructure crucial for AI/ML operations, and you will collaborate with AI/ML engineers and researchers to develop a robust CI/CD pipeline that supports safe and reproducible experiments. Your expertise will also extend to setting up and maintaining monitoring, logging, and alerting systems to oversee extensive training runs and client-facing APIs. You will ensure that training environments are optimally available and efficiently managed across multiple clusters, enhancing our containerization and orchestration systems with advanced tools like Docker and Kubernetes.
This role demands a proactive approach to maintaining large Kubernetes clusters, optimizing system performance, and providing operational support for our suite of software solutions. If you are driven by challenges and motivated by the continuous pursuit of innovation, this role offers the opportunity to make a significant impact in a dynamic, fast-paced environment.
????️ Your responsibilities:

• Work closely with AI/ML engineers and researchers to design and deploy a CI/CD pipeline that ensures safe and reproducible experiments.
• Set up and manage monitoring, logging, and alerting systems for extensive training runs and client-facing APIs.
• Ensure training environments are consistently available and prepared across multiple clusters.
• Develop and manage containerization and orchestration systems utilizing tools such as Docker and Kubernetes.
• Operate and oversee large Kubernetes clusters with GPU workloads.
• Improve reliability, quality, and time-to-market of our suite of software solutions
• Measure and optimize system performance, with an eye toward pushing our capabilities forward, getting ahead of customer needs, and innovating for continual improvement
• Provide primary operational support and engineering for multiple large-scale distributed software applications
  

️ Is this you?

• You have professional experience with:
• Model training
• Huggingface Transformers
• Pytorch
• vLLM
• TensorRT
• Infrastructure as code tools like Terraform
• Scripting languages such as Python or Bash
• Cloud platforms such as Google Cloud, AWS or Azure
• Git and GitHub workflows
• Tracing and Monitoring
• Familiar with high-performance, large-scale ML systems
• You have a knack for troubleshooting complex systems and enjoy solving challenging problems
• Proactive in identifying problems, performance bottlenecks, and areas for improvement
• Take pride in building and operating scalable, reliable, secure systems
• Familiar with monitoring tools such as Prometheus, Grafana, or similar
• Are comfortable with ambiguity and rapid change
  

Preferred skills and experience:

• Familiar with monitoring tools such as Prometheus, Grafana, or similar
• 5+ years building core infrastructure
• Experience running inference clusters at scale
• Experience operating orchestration systems such as Kubernetes at scale
  

Benefits & Perks (US Full-time Employees)

• Generous PTO, plus company holidays
• Medical, dental, and vision coverage for you and your family
• Paid parental leave for all parents (12 weeks)
• Fertility and family planning support
• Early-detection cancer testing through Galleri
• Flexible spending account and dependent FSA options
• Health savings account for eligible plans with company contribution
• Annual work-life stipends for:
• Home office setup, cell phone, internet
• Wellness stipend for gym, massage/chiropractor, personal training, etc.
• Learning and development stipend
• Company-wide off-sites and team off-sites
• Competitive compensation, company stock options and 401k
  

Writer is an equal-opportunity employer and is committed to diversity. We don't make hiring or employment decisions based on race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other basis protected by applicable local, state or federal law. Under the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
By submitting your application on the application page, you acknowledge and agree to Writer's Global Candidate Privacy Notice.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  Software Development

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