Machine Learning Engineer, Enterprise Brain

About the role

The Enterprise Brain team is developing a suite of proactive AI products that aim to revolutionize enterprise workflows by proactively detecting and automating tasks for users - thus unlocking true productivity. This involves using both Large Language Models (LLM) and other advanced ML techniques, agent orchestration, and cutting-edge ranking techniques.

Responsibilities

• Work on deeply challenging ML problems involving user understanding and task prediction.
• Invent new LLM workflows and signals to improve reasoning, planning, and personalization.
• Design and optimize reinforcement learning and fine-tuning approaches to improve the quality of understanding, prediction, and other agentic systems.
• Lead development of scalable evaluation, benchmarking, and optimization loops.
• Build and maintain robust ML pipelines for enterprise and knowledge graph construction.
• Drive initiatives to measure, monitor, and improve data quality, model quality, and end-to-end system performance.
• Collaborate with cross-functional teams to deeply understand customer pain points and deliver high-quality, production-ready ML solutions.
• Mentor junior engineers or learn from experienced ones in a tight-knit, high-velocity environment.

Requirements

• 3+ years of industry experience in AI or Machine Learning Engineering.
• Bachelor's degree in computer science, math, sciences, or a related field.
• Experience with search, recommendation, natural language processing, or other large-scale ML systems.
• Proven ability to design, build, and ship production-ready models and systems.
• Demonstrated expertise in ML evaluation, benchmarking, and data quality—ideally with experience in building or maintaining evaluation frameworks for complex enterprise tasks.
• Proficiency in your ML framework of choice (e.g., TensorFlow, PyTorch).
• Strong coding skills (Python, Go, Java, C++, etc.).
• Thriving in a customer-focused, cross-functional environment; a proactive and positive attitude is a must.

Qualifications

• Experience with large-scale enterprise applications and knowledge graphs.
• Knowledge of reinforcement learning and its applications in enterprise settings.
• Experience with agent orchestration and ranking techniques.

Skills

• Deep understanding of machine learning algorithms and their practical applications.
• Experience with large-scale data processing and analysis.
• Ability to work effectively in a fast-paced, agile environment.
• Strong problem-solving and analytical skills.

Benefits

We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused.

Pay

The standard base salary range for this position is $200,000 - $300,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.

Schedule

This role is hybrid (4 days a week in our Mountain View, CA office).