Senior Software Engineer - ML Infrastructure

FDE Times; Sunnyvale (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Equity

Health Insurance

Dental Insurance

Vision Insurance

Life Insurance

Disability Insurance

401(k) With Employer Match

Learning Stipend

Wellness Stipend

Paid Time Off

Job summary

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

Qualifications

• 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.

Responsibilities

• 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.

Skills

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

Education

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

Job description

Design distributed cloud GPU training approaches and build end-to-end machine learning pipelines spanning dataset generation, training, evaluation, and deployment. Collaborate with modeling and engineering teams to solve large-scale data problems and improve machine learning engineering practices and product workflows.

Requirements: Requires a bachelor's degree in computer science, software engineering, or an equivalent field, at least three years of professional experience, and experience building production software for full-stack machine learning challenges. Candidates should have strong analytical and problem-solving skills, sound judgment about open-source versus in-house tools, and opinions on company-wide ML platforms; experience with orchestration, modeling frameworks, and model-serving platforms is a plus.

Key Skills: 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

Benefits: Equity, Health Insurance, Dental Insurance, Vision Insurance, Life Insurance, Disability Insurance, 401(k) With Employer Match, Learning Stipend, Wellness Stipend, Paid Time Off