Software Engineer, Research Acceleration

6 months ago

H1B Sponsor

Base Salary

$350k - $475k/yr

Responsibilities

Design, build, and operate research infrastructure including evaluation frameworks, RL training systems, experiment tracking platforms, visualization tools, and shared utilities.
Develop high-throughput, scalable pipelines for distributed evaluation, reward modeling, and multimodal assessment.
Build reproducibility, traceability, quality control, monitoring, and observability systems for research experiments and model training runs.
Partner directly with researchers to identify bottlenecks, unlock capabilities, gather feedback, and track tooling adoption.
Collaborate with infrastructure, data, and product teams to integrate tools across the technical stack.

Bachelor’s degree or equivalent experience in computer science, engineering, machine learning, or a similar field.
Strong software engineering fundamentals and a track record of building reliable, maintainable systems.
Proficiency in at least one backend language, specifically Python or Rust.
Ability to operate across the stack and own projects end to end.
Experience working collaboratively with cross-functional partners and subject matter experts.
Preferred experience building tooling for researchers that achieved high adoption.
Preferred experience with ML research infrastructure such as training frameworks, evaluation libraries, or experiment tracking systems.
Open-source contributions or widely used internal frameworks at research-focused organizations are preferred.
Publications or technical writing on ML systems, infrastructure, or tooling are preferred.
Background working closely with ML researchers is preferred.
Familiarity with distributed systems, PyTorch, JAX, Ray, Spark, research observability tools, and large-scale evaluation pipelines is preferred.