Member of Technical Staff, Machine Learning

About Us

We aim to revolutionize the way more than 5 billion users interact with common applications like email, notes, and tasks by creating an intelligent assistant that enhances conversations, errands, organizing, and workflows with minimal user input. Our product prioritizes high reliability for long-duration workflows and persistent context, capable of handling complex multi-step reasoning and tool interaction while maintaining dependable performance despite the unpredictable nature of AI models. Our goal is to significantly reduce users' time spent on daily tasks by over 90%.

Role overview

As a Member of Technical Staff specializing in Machine Learning, you will be directly involved in developing key machine learning components and working on operational production systems from the outset. This role is tailored for engineers eager to build strong practical system skills through real-world ML deployment, debugging, and iterative development.

Core Responsibilities

• Develop and enhance machine learning modules spanning data processing, training, evaluation, and inference phases.
• Fine-tune and adjust models integrated within broader production environments.
• Create and implement testing frameworks to analyze model behaviors.
• Develop and maintain robust data pipelines for both real and synthetic datasets.
• Identify and troubleshoot model performance issues and production incidents promptly.
• Continuously improve system features by shipping updates and learning from end-user feedback.
• Collaborate closely with senior ML engineers and cross-functional product teams.
• Balance production constraints such as latency, cost efficiency, reliability, and safety.

Technology Stack

• Proficient in Python programming.
• Experience with ML frameworks like PyTorch and JAX.
• Knowledge of deploying ML models on GPU-based production systems.

Desired Qualifications and Traits

• Strong theoretical foundation in machine learning and contemporary neural network architectures.
• Practical experience in training, fine-tuning, or deploying machine learning models.
• Ability to produce production-level code and quickly adapt to new software tools.
• Eagerness to learn from production systems, demonstrating curiosity and coachability.
• Comfortable navigating ambiguity with mentorship while growing into autonomous responsibility.
• A proactive approach favoring fast iteration, shipping, and continuous enhancement.

Expected Outcomes

• Deliver ML models in production that meet stringent accuracy, latency, and reliability benchmarks.
• Effectively diagnose and resolve production issues, addressing root causes swiftly.
• Ensure data pipelines, training procedures, and inference mechanisms are stable, reproducible, and maintainable.
• Work well with engineering, product, and research teams for reliable delivery of ML-powered features.
• Drive iterative model refinements based on tangible real-world metrics and user feedback.

Work Culture

We operate in a small, highly skilled, and hands-on team environment where rapid decision-making and balance between high-quality output and learning are crucial. Joining requires individuals who can organize, exercise sound judgment, and work independently. Our collective ambition is to provide users with truly transformative AI-powered products.

Interview Process

The selection involves up to four interviews conducted virtually or onsite by our technical staff. We value clear communication and swift decisions. Candidates demonstrating the required exceptional skills and mindset will receive an offer to join our team focused on delivering impactful AI solutions to billions worldwide.