Senior ML Workflow Architect

Weights & Biases; Livingston (NJ); On-site; USD 180,000 - 230,000; 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 senior software engineer to own the architecture and evolution of core ML workflow systems, including Artifacts, Registry, and Automations. You will design scalable systems handling billions of artifacts and high-volume event throughput across the full stack.

Requirements include 6+ years of software engineering, strong Go or compiled language skills with Python, and a track record of leading technical initiatives and mentoring other engineers.

Qualifications

• 6+ years of software engineering experience with leadership.
• Proficiency in Go or another compiled language and Python.
• Experience mentoring engineers and leading technical initiatives.

Responsibilities

• Own the architecture and evolution of ML workflow systems such as Artifacts, Registry, and Automations.
• Design and scale systems for billions of artifacts and high-throughput events.
• Drive technical initiatives and mentor engineers across the team.

Skills

Go

Python

TypeScript

React

GraphQL

Distributed Systems

Kubernetes

ClickHouse

Kafka

PubSub

API Design

System Architecture

MLOps

Software Engineering

Mentoring

Cloud Infrastructure

Tools

Kubernetes

ClickHouse

Kafka

PubSub

Job description

Weights & Biases is seeking an senior software engineer to own the architecture and evolution of core ML workflow systems, including Artifacts, Registry, and Automations. You will design scalable systems handling billions of artifacts and high-volume event throughput across the full stack.

Requirements include 6+ years of software engineering, strong Go or compiled language skills with Python, and a track record of leading technical initiatives and mentoring other engineers.