ML Engineer – AI Agent Platform (Hybrid)

Superhuman; San Francisco (CA); Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Health care

Insurance (Disability & Life)?

401(k) matching

Parental leave

Paid time off & holidays

Professional development budget

Job summary

Superhuman is building a platform for AI Agents, and as a Machine Learning Engineer you will help accelerate the transformation by integrating advanced ML models into product experiences and shaping an AI-native productivity suite for enterprises.

You will own core ML systems, architect the orchestration and planning components, and collaborate with cross-functional teams in a fast-paced, autonomous environment to deliver impactful features at scale.

Qualifications

• MS / PhD in Computer Science.
• 5+ years of industry experience as a machine learning engineer or applied research scientist.
• Deep understanding of modern algorithms and approaches to ML, NLP, and LLMs.
• Experience building LLM-based products.
• End-user focus and quality-oriented mindset.
• Ability to work independently with minimal guidance and manage priorities across multiple projects.

Responsibilities

• Shape the future of productivity by evolving Grammarly into an indispensable, AI-native productivity suite for enterprises.
• Build a groundbreaking AI Agent platform with core orchestration, routing, and planning systems.
• Own and deploy sophisticated ML models across core product experiences, including search ranking and proactive suggestions.
• Integrate cutting-edge AI by building ML components that leverage the latest models for magical user experiences.
• Operate with autonomy in a fast-paced, ambiguous environment and ship impact-driven work quickly.

Skills

ML engineering

NLP & LLMs

Independent work

Cross-functional collaboration

Product-focused mindset

Education

MS/PhD in Computer Science

Job description

Superhuman is building a platform for AI Agents, and as a Machine Learning Engineer you will help accelerate the transformation by integrating advanced ML models into product experiences and shaping an AI-native productivity suite for enterprises.

You will own core ML systems, architect the orchestration and planning components, and collaborate with cross-functional teams in a fast-paced, autonomous environment to deliver impactful features at scale.