Machine Learning Engineer

Superhuman offers a dynamic hybrid working model for this role. This flexible approach gives team members the best of both worlds: plenty of focus time along with in-person collaboration that helps foster trust, innovation, and a strong team culture. The Opportunity We are building a platform for AI Agents to come together and solve arbitrarily complex tasks, leveraging Superhuman ubiquitous UI. As a Machine Learning Engineer on this team, you will be at the heart of our company's transformation. • Shape the Future of Productivity: Play a pivotal role in evolving Grammarly from a beloved writing assistant into an indispensable, AI-native productivity suite for enterprises. • Build a Groundbreaking AI Agent Platform: Spearhead the development of a new platform where multiple AI agents collaborate to solve complex user problems. You will be responsible for the core orchestration, routing, and planning systems. • Own Critical ML Systems: Develop and deploy sophisticated ML models for core product experiences, including search ranking and proactive suggestions that anticipate user needs. • Integrate Cutting-Edge AI: Work at the forefront of the AI landscape, building ML components that integrate with the latest and most powerful models to create magical user experiences. • Thrive in a High-Impact Environment: Join a foundational team where you will operate with a high degree of autonomy and product sense in a fast-paced, ambiguous environment. • Ship Your Work Fast: Move quickly from idea to impact. We have no red tape or endless approvals-just a focus on making meaningful contributions to a platform used by millions. What You'll Work On • The core orchestration. Users connect many apps and agents, and their requests can take many steps. Some steps run in the background while nobody is watching. You'll own how the agent plans the work, picks the right agent or tool for each step, and sees long tasks through to the end. • Memory and action. You'll keep long conversations useful, and decide what the agent should remember about a user. The agent also takes actions for users, and you'll widen what it can do while keeping the user in control. • Search and proactive suggestions. The answer is often spread across a user's email, messages and documents. You'll build the ML models that find it and rank it. You'll also build the suggestions that point out what matters before the user asks. • Quality, speed and cost. Every change has to prove it helps before it ships, so designing evals is as much a part of the job as designing models. You'll also make the agent faster and cheaper to run without making its answers worse. Qualifications • MS / PhD in Computer Science. • 5+ years of industry experience as a machine learning engineer or applied research scientist. • A deep understanding of modern algorithms and approaches to ML, NLP, and LLMs. • Experience building LLM-based products. • A deep care about the end-user experience and strives to ensure high quality. • Has a demonstrated ability to work independently with minimal guidance, proactively manages tasks and priorities across multiple projects, analyzes and executes work efficiently, collaborates effectively with cross-functional teams, and thrives in fast-paced, results-driven environments. We invite you to share your knowledge, experience, and goals with us to help us find the best team match for you. Tell us your superpower! Compensation and Benefits Superhuman offers all team members competitive pay along with a benefits package encompassing the following and more: • Excellent health care (including a wide range of 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 days of paid holidays per year, two floating holidays per year, and flexible sick time • Generous stipends (including those for caregiving, pet care, wellness, your home office, and more) • Annual professional development budget and opportunities Superhuman takes a market-based approach to compensation, which means base pay may vary depending on your location. Our US locations are categorized into two compensation zones based on proximity to our hub locations.