Senior Software Engineer, ML Workflows - Weights & Biases

Quick Facts

Senior Software Engineer reporting to the Senior Engineering Manager for ML Workflows. Own the architecture and evolution of core systems in the Weights & Biases platform, from design through production reliability.

Description

ML Workflows owns what customers use to move models and data through W&B. Artifacts is the versioned data layer that every logged object runs through; Registry is the organization-wide source of truth for what is production-ready. Automations provides the event/action layer, and Launch provides execution infrastructure for customer ML and agent workloads.

You will own systems end to end, working across the W&B backend, the Python SDK, and the frontend, partnering with product managers, designers, and ML platform engineers, and talking directly with enterprise ML teams about their workflows.

Responsibilities

• Own the architecture and evolution of a core platform area; design systems that scale to billions of artifacts and high-volume event and job throughput.
• Dive deep into system architecture to find optimization opportunities, solve complex bugs, and make tradeoffs between short-term delivery and long-term platform health.
• Work across the stack as required: Go backend services and GraphQL APIs, the Python SDK, and the TypeScript frontend.
• Lead migrations and re-architecture of systems carrying live customer traffic, keeping customer experience seamless.
• Identify and refactor technical debt to improve maintainability and developer productivity.
• Establish engineering patterns and best practices that scale as the platform grows.
• Collaborate with product and design to turn complex user requirements into clean technical implementations.
• Work directly with customers to understand ML workflow challenges and feed that feedback into the product cycle.
• Mentor engineers and raise the technical bar across the team.

Requirements

• Bachelor’s degree or foreign equivalent in Computer Science, Computer Engineering, Data Science, Information Systems, or a closely related technical/quantitative field with substantial coursework in Engineering.
• 6+ years of software engineering experience, including time leading significant technical initiatives or architectural changes.
• Strong proficiency in Go, or ability to ramp on Go quickly from another compiled language (C, C++, C#, Rust, Java).
• Working proficiency in Python.
• Comfort debugging complex systems not originally authored to diagnose and fix difficult bugs across service boundaries.
• Track record of mentoring engineers and raising the technical bar.
• Strong communication skills to explain complex technical decisions to different audiences.
• Depth in at least one or two areas: distributed systems/infrastructure; frontend/full-stack (TypeScript, React, state management, performance); data at scale (schema design, query performance, large-scale storage, ClickHouse); APIs/developer surfaces (API design, GraphQL optimization, data fetching strategies, SDKs/client libraries); event-driven systems (Kafka or PubSub, delivery semantics, idempotency, retries).
• Experience in ML infrastructure, MLOps, or developer tools is a plus.
• Ability to access export-controlled information (U.S. person or eligible to obtain required authorization).

Benefits

• Medical, dental, and vision insurance (100% paid)
• Company-paid Life Insurance
• Voluntary supplemental life insurance
• Short and long-term disability insurance
• Flexible Spending Account
• Health Savings Account
• Tuition Reimbursement
• Employee Stock Purchase Program (ESPP)
• Mental Wellness Benefits through Spring Health
• Family-Forming support (Carrot)
• Paid Parental Leave
• Flexible, full-service childcare support (Kinside)
• 401(k) with generous employer match
• Flexible PTO
• Catered lunch each day in office and data center locations
• Casual work environment
• Culture focused on innovative disruption

Compensation

Base pay and target total cash range: $165,000–$220,000. Starting salary is determined by job-related knowledge, skills, experience, and market location. Total rewards include discretionary bonus, equity awards, and a comprehensive benefits program (eligibility-based).