Senior ML Workflows Engineer — Scale Pipelines & Mentor

Weights & Biases

Sunnyvale (CA)

On-site

USD 180,000 - 240,000

Full time

3 days ago
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Benefits offered by this job

Medical insurance
Dental insurance
Vision insurance
Company-paid Life Insurance
Voluntary supplemental life insurance
Short and long-term disability insur.
Flexible Spending Account
Health Savings Account
Tuition Reimbursement
Employee Stock Purchase Program (ESPP)
Mental Wellness Benefits
Family-Forming support
Paid Parental Leave
Flexible 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.

Designing scalable, high-throughput systems across the full stack—from Go backends to TypeScript frontends—will be core to the role. You will lead technical initiatives and mentor other engineers while collaborating with cross-functional teams.

Qualifications

  • 6+ years of software engineering experience with Go or another compiled language and Python.
  • Track record of leading technical initiatives and mentoring other engineers.
  • Strong knowledge of distributed systems and modern cloud infrastructure.

Responsibilities

  • Own the architecture and evolution of core ML workflow systems like Artifacts, Registry, and Automations.
  • Design scalable systems for high-volume event throughput across the full stack (Go backends to TypeScript frontends).
  • Collaborate with teams across engineering, data, and product to deliver reliable systems.

Skills

Go
Python
TypeScript
React
GraphQL
Distributed Systems
Kubernetes
ClickHouse
Kafka
PubSub
System Architecture
API Design
MLOps
Cloud Infrastructure
Software Engineering
Mentoring

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.

Designing scalable, high-throughput systems across the full stack—from Go backends to TypeScript frontends—will be core to the role. You will lead technical initiatives and mentor other engineers while collaborating with cross-functional teams.

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