ML Infra Engineer

2 weeks ago
Full-time
Mid Level
DevOps and Infrastructure
Lever

Lever

Lever is a leading Talent Acquisition Suite that provides modern hiring and talent management solutions. Their applicant tracking system (ATS) with candidate relationship management capabilities empowers hiring teams to streamline recruiting efforts an...

Professional Services
251-1K
Founded 2012
$123M raised

Description

  • Work on data collection infrastructure that reliably transfers sensor data from vehicles into the ML platform.
  • Develop batch compute pipelines to catalog, explore, and curate raw data into high-quality training sets.
  • Design and scale distributed ML training on GPU clusters.
  • Own performance, observability, efficiency, and security across the full ML infrastructure pipeline.
  • Partner with the ML team to translate workflows into reliable infrastructure that accelerates their work.
  • Help design, build, and scale foundational systems across vehicle compute, data collection, dataset curation, training, and deployment.
  • Contribute to technical and organizational decisions that shape the company’s infrastructure direction.

Requirements

  • Experience building and operating high-availability web services on cloud infrastructure.
  • Experience with infrastructure-as-code and configuration management tools, including Terraform and Ansible.
  • Experience building and maintaining CI/CD pipelines and managing deployments.
  • Strong security fundamentals, including Linux hardening, network security, and cryptographic principles.
  • Hands-on experience with cluster scheduling systems for large-scale batch computation.
  • Comfort reading, writing, and extending non-trivial code beyond simple scripting.
  • Eligibility to work in the United States.
  • Hands-on experience managing large, high-performance ML training clusters (preferred).
  • Working knowledge of distributed training frameworks and high-performance networking for ML workloads (preferred).
  • Prior infrastructure experience at an early-stage autonomous vehicle or robotics company (preferred).
  • Ability to operate as an early team member with high ownership, low ego, and fast iteration (preferred).

Benefits

  • Base salary plus benefits and equity compensation.
  • Salary range determined by role, level, and location.
  • Pay is also influenced by qualifications, skills, experience, and location.
  • Equal opportunity employer consideration for all qualified applicants.

Interested in this position?

Apply directly on the company website

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