Senior ML Infrastructure Engineer: Cloud GPU & Pipelines

FDE Times; Sunnyvale (CA); Presencial; USD 150.000 - 210.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Equity

Health Insurance

Dental Insurance

Vision Insurance

Life Insurance

Disability Insurance

401(k) With Employer Match

Learning Stipend

Wellness Stipend

Paid Time Off

Descripción de la vacante

FDE Times in Sunnyvale, CA seeks a design-focused machine learning engineer to design distributed cloud GPU training approaches and build end-to-end ML pipelines spanning dataset generation, training, evaluation, and deployment. You will collaborate with modeling and engineering teams to solve large-scale data problems and improve ML engineering practices and product workflows.

A bachelor's degree and 3+ years of production ML experience are required; experience with orchestration, modeling

Formación

• Requires a bachelor's degree in computer science, software engineering, or an equivalent field.
• At least three years of professional experience.
• Experience building production software for full-stack machine learning challenges.

Responsabilidades

• Design distributed cloud GPU training approaches.
• Build end-to-end ML pipelines spanning dataset generation, training, evaluation, and deployment.
• Collaborate with modeling and engineering teams to improve ML engineering practices and product workflows.

Conocimientos

Machine Learning Infrastructure

Distributed GPU Training

Machine Learning Pipelines

Deep Learning

Cloud Computing

Dataset Generation

Model Evaluation

Model Deployment

Production Machine Learning

Data Engineering

Airflow

Flyte

PyTorch

TensorFlow

TorchServe

NVIDIA Triton

Educación

Bachelor's degree in Computer Science, Software Engineering, or equivalent

Descripción del empleo

FDE Times in Sunnyvale, CA seeks a design-focused machine learning engineer to design distributed cloud GPU training approaches and build end-to-end ML pipelines spanning dataset generation, training, evaluation, and deployment. You will collaborate with modeling and engineering teams to solve large-scale data problems and improve ML engineering practices and product workflows.

A bachelor's degree and 3+ years of production ML experience are required; experience with orchestration, modeling