Remote Distributed Rust Engineer for Data & ML

tensorlake.ai

United States

Remote

USD 140,000 - 180,000

Full time

7 days ago
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Job summary

tensorlake.ai is building the core runtime for data processing and ML workloads. You will design and implement infrastructure used by other engineers to run workloads, covering scheduling, execution, and performance.

You will evolve the runtime, design efficient scheduler components, and implement core data plane elements in Rust or other systems languages. This role involves contributing across the full product lifecycle from exploration through delivery.

Qualifications

  • Five+ years designing and building distributed systems infrastructure.
  • Production experience with Rust or another systems language.
  • Experience with schedulers, databases, or runtimes through build or contribution.
  • Ability to independently design and deliver fault-tolerant systems.
  • Interest in low-level performance work (memory, concurrency, networking).
  • Willingness to contribute across product development from research to implementation.

Responsibilities

  • Evolve the runtime to support advanced data and ML workflows.
  • Design scheduler components to improve cluster resource use, cost, and performance.
  • Build data plane and execution engine components in Rust or similar.
  • Develop new capabilities for software development kits.
  • Take engineering ideas from exploration to polished product delivery.

Skills

Distributed systems design
Rust
Schedulers
Fault-tolerant systems
Performance optimization

Tools

FoundationDB
Python
TypeScript
Go

Job description

tensorlake.ai is building the core runtime for data processing and ML workloads. You will design and implement infrastructure used by other engineers to run workloads, covering scheduling, execution, and performance.

You will evolve the runtime, design efficient scheduler components, and implement core data plane elements in Rust or other systems languages. This role involves contributing across the full product lifecycle from exploration through delivery.

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