Senior ML Workflow Architect: Scalable Systems (Go/Python)

Weights & Biases; Seattle (WA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Company-paid Life Insurance

Voluntary Supplemental Life Insurance

Short-term Disability Insurance

Long-term Disability Insurance

Flexible Spending Account

Health Savings Account

Tuition Reimbursement

Employee Stock Purchase Program (ESPP)

Mental Wellness Benefits

Family-Forming Support

Paid Parental Leave

Childcare Support

401(k) with Employer Match

Flexible PTO

Catered Lunch

Job summary

Weights & Biases is seeking an experienced software engineer to own the architecture and evolution of core ML workflow systems, including Artifacts, Registry, and Automations.

You will design scalable systems for high-volume event throughput and collaborate across the stack from backend services to the frontend UI, applying expertise in distributed systems, data at scale, and event-driven architectures.

Qualifications

• Requires 6+ years of software engineering experience with strong proficiency in Go or another compiled language and working knowledge of Python.
• Candidates must have a track record of mentoring engineers and deep expertise in areas like distributed systems, data at scale, or event-driven architectures.

Responsibilities

• Own the architecture and evolution of core ML workflow systems, including Artifacts, Registry, and Automations.
• Design scalable systems for high-volume event throughput and collaborate across the stack from backend services to the frontend UI.

Skills

Go

Python

TypeScript

React

GraphQL

Distributed Systems

Kubernetes

ClickHouse

Kafka

PubSub

API Design

System Architecture

MLOps

ML Infrastructure

Full-stack Development

Software Engineering

Tools

Kubernetes

ClickHouse

Kafka

PubSub

GraphQL

API Design

System Architecture

Job description

Weights & Biases is seeking an experienced software engineer to own the architecture and evolution of core ML workflow systems, including Artifacts, Registry, and Automations.

You will design scalable systems for high-volume event throughput and collaborate across the stack from backend services to the frontend UI, applying expertise in distributed systems, data at scale, and event-driven architectures.