Machine Learning Engineer, Enterprise Brain

Description

The company builds a Work AI platform that combines enterprise search, an AI assistant, and AI agents on one secure, open system. It connects to more than 100 enterprise SaaS tools, lets customers choose their LLM, and offers APIs for governing and customizing AI without vendor lock-in.

Its Enterprise Graph and Personal Knowledge Graph link people, content, and activity so responses fit each employee's context. Agents use enterprise and public data, both structured and unstructured, past and live, to automate work across teams.

The company has more than 1,000 employees in over 25 countries and serves customers in 50+ industries.

The Enterprise Brain team builds applied ML systems that understand a user's work and predict useful next steps, such as tasks and proactive help. The team mixes LLMs, traditional ML, Enterprise Graph signals, ranking and retrieval, and orchestration, and focuses on measurable gains in product quality.

Responsibilities

• Frame and solve applied ML problems around understanding user work, predicting tasks, and offering proactive help.
• Combine LLMs, traditional ML, Enterprise Graph signals, ranking and retrieval, and orchestration to raise product quality.
• Build and ship production ML systems, along with the evaluation, benchmarking, and data-quality processes that show their impact.
• Take ownership from problem definition and baseline through launch, monitoring, and ongoing iteration.
• Work with product and engineering to understand customer problems and deliver reliable solutions ready for production.

Requirements

• You have 6+ years of industry experience in machine learning engineering.
• You hold a BA or BS in computer science, math, a science, or a related field.
• You have a record of designing, building, and shipping production-ready models and systems.
• You have solid experience with ML evaluation, benchmarking, and data quality.
• You are skilled in an ML framework of your choice, such as TensorFlow or PyTorch.
• You can work in a fast-changing, ambiguous setting, turning open-ended customer and ML problems into clear priorities and production-ready solutions.
• You weigh speed against quality, making practical tradeoffs that deliver measurable progress while keeping production readiness in view.

Conditions

This role is hybrid, with 4 days a week in the Mountain View office.

The standard base salary range is $200,000 - $280,000 per year. Final pay depends on factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.

The interview includes a short AI-focused exercise or discussion about how you think about, design, and use AI. You may reference any tools, platforms, or workflows you use today. Prior the company experience is not required.

The company is committed to a diverse, inclusive workplace and does not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.

Benefits

• Competitive compensation, plus medical, vision, and dental coverage.
• Generous time off.
• A 401k plan you can contribute to for long-term savings.
• A home office improvement stipend when you join.
• An annual education stipend and an annual wellness stipend.
• Regular company events and healthy lunches provided daily.