Machine Learning Engineer

Superhuman • San Francisco, CA

42d • $250,000 - $385,000 • Hybrid

About The Position

Superhuman is building a platform for AI agents to collaborate on complex tasks through its ubiquitous user interface. The Machine Learning Engineer will help develop this platform and contribute to the company's transformation into an AI-native productivity suite. The role focuses on core agent orchestration, routing, and planning; developing and deploying machine learning models for search ranking and proactive suggestions; and integrating ML components with current AI models. The engineer will work on a foundational team with substantial autonomy in a fast-paced, ambiguous environment, moving ideas quickly into products used by millions.

The work includes planning multistep requests across connected apps and agents, selecting the right agent or tool for each step, and ensuring long-running tasks reach completion. The engineer will develop memory and action capabilities that keep conversations useful, determine what the agent should remember, and expand the actions it can take while keeping users in control. They will build models to find and rank information across users' email, messages, and documents, and create proactive suggestions. They will also design evaluations to establish whether changes improve quality and make the agent faster and less expensive without degrading its answers.

Requirements

• MS or PhD in Computer Science.
• At least 5 years of industry experience as a machine learning engineer or applied research scientist.
• Deep understanding of modern machine learning, natural language processing, and large language model algorithms and approaches.
• Experience building products based on large language models.
• Strong care for the end-user experience and commitment to high quality.
• Ability to work independently with minimal guidance, proactively manage tasks and priorities across multiple projects, analyze and execute work efficiently, collaborate effectively with cross-functional teams, and thrive in fast-paced, results-driven environments.

Responsibilities

• Develop core orchestration, routing, and planning systems for a platform where AI agents collaborate on complex tasks.
• Build systems that plan multistep work, select the appropriate agent or tool for each step, and manage long-running tasks through completion.
• Develop memory capabilities that keep long conversations useful and determine what the agent should remember about users.
• Expand the actions agents can take while keeping users in control.
• Build machine learning models for search and ranking across users' email, messages, and documents.
• Build proactive suggestions that surface relevant information before users ask.
• Integrate machine learning components with leading AI models.
• Design evaluations to measure whether product and model changes improve quality before release.
• Improve agent speed and cost without reducing answer quality.

Benefits

• Competitive pay.
• Medical, dental, vision, mental health, and fertility benefits.
• Disability and life insurance options.
• 401(k) and RRSP matching.
• Paid parental leave.
• 20 days of paid time off per year, 12 paid holidays per year, two floating holidays per year, and flexible sick time.
• Stipends, including for caregiving, pet care, wellness, and home office expenses.
• Annual professional development budget and opportunities.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior