ML Infrastructure Engineer

3 months ago

H1B Sponsor

Base Salary

$180k - $230k/yr

Responsibilities

Create flexible and performant ML infrastructure.
Design and build systems for ML cloud infrastructure to enable massive-scale modeling and analytics.
Support diverse model exploration, hyperparameter optimization, pretraining, fine-tuning, and evaluation processes.
Design and optimize scalable distributed training pipelines.
Create, operate, and maintain robust ML platforms and services across the model lifecycle.
Make informed architecture decisions balancing performance, cost, reliability, and scalability.
Design, build, and optimize massive-scale databases and data pipelines.
Explore research-driven, tailored data solutions using existing and simulated data.
Create infrastructure and pipelines for ingesting internal and external datasets.
Design and assess custom data formats for efficient storage of high-dimensional time-series data.
Establish best practices for reliability, observability, reproducibility, and operational excellence.
Foster visibility and reproducibility by maintaining extensive documentation of design decisions.

Bachelor's degree in Computer Science, Electrical Engineering, or a related technical discipline.
5+ years of industry experience in software engineering, large-scale data infrastructure, or systems ML.
Extensive proficiency in Python.
Familiarity with PyTorch.
Experience designing, building, and maintaining high-throughput data pipelines.
Experience working with distributed-training frameworks.
Demonstrated ability to partner closely with research and modeling teams.
Excellent communication and collaboration skills.
Experience having technical ownership over a successfully implemented collaborative project.

C++DockerGoJavaKubernetesPythonPyTorchRust