Senior ML Infrastructure Engineer - GPU Training & MLOps

Atoms; San Francisco (CA); On-site; USD 224,000 - 280,000; Full time

Benefits offered by this job

Medical, Dental, Vision, Disability, and Life Insurance

Flexible Spending Account / Health Savings Account Options

401(k)

Unlimited Flexible Time Off

Team lunch every Tuesday and Thursday

Job summary

Atoms, based in San Francisco, is seeking a Machine Learning Infrastructure Engineer to design the ML training infrastructure for autonomous transport models. The role involves scaling distributed GPU workloads, leading to innovations across their platform.

Ideal candidates should have over 8 years of software engineering experience and be proficient in technologies such as Kubernetes, Go, and Python. The position is fully onsite and offers benefits like medical insurance, equity, and more.

Qualifications

• 8+ years of professional software engineering experience.
• Strong backend systems programming skills.
• Proficiency in Kubernetes and distributed compute frameworks.

Responsibilities

• Design and build large-scale ML training infrastructure.
• Implement and scale ML infrastructure using Kubernetes.
• Build high-throughput data ingestion pipelines.

Skills

Go

Python

Java

Kubernetes

Distributed ML frameworks

MLOps pipelines

Metadata tracking

Data engineering

Job description

Atoms, based in San Francisco, is seeking a Machine Learning Infrastructure Engineer to design the ML training infrastructure for autonomous transport models. The role involves scaling distributed GPU workloads, leading to innovations across their platform.

Ideal candidates should have over 8 years of software engineering experience and be proficient in technologies such as Kubernetes, Go, and Python. The position is fully onsite and offers benefits like medical insurance, equity, and more.