Lead ML Engineer

🕒 March 31

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Intuition Machines

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2014

🤖 Artificial Intelligence

🔒 Cybersecurity

☁️ SaaS

Artificial Intelligence • Cybersecurity • SaaS

Intuition Machines is a leader in machine intelligence, specializing in privacy-preserving AI platforms and research. The company provides AI/ML products and services to some of the largest online services worldwide, focusing on scaling and solving complex problems using machine learning. Intuition Machines develops innovative solutions like the hCaptcha Security Suite, which is used by enterprises globally to protect hundreds of millions of people with its privacy-first approach to security AI. The firm's offerings include the IM Perception Platform, which automates the train-deploy-improve cycle with a focus on active learning and robust APIs. Additionally, Intuition Machines engages in cutting-edge AI/ML research, contributing to advances in security machine learning, fraud detection, and data privacy. The company also collaborates with top online payment processors, offering models with high precision and almost zero false positives, without using personally identifiable information. Notably, Cloudflare has chosen Intuition Machines' hCaptcha Enterprise for securing a significant portion of internet sites.

📋 Description

• Lead large-scale ML projects and products from inception to production, overseeing the entire lifecycle from design and implementation to deployment and maintenance. • Make key architectural decisions to ensure solutions are scalable, efficient, and maintainable while balancing business and technical constraints. • Drive collaboration across ML and engineering teams to ensure product success, influencing technical discussions and decisions at all levels. • Design and implement state-of-the-art machine learning pipelines and models that impact millions of users and generate real business value. • Set technical standards and lead the development of scalable, testable, and high-performance applications. • Provide leadership and mentorship to other ML engineers, fostering the growth of a strong Machine Learning Engineering organization. • Work on systems that affect millions of users daily, scaling machine learning systems with billions of data points and millions of inferences per second. • Gain experience in architecting and scaling advanced ML solutions for real-world challenges, moving beyond standard approaches from research papers. • Have the opportunity to define technical strategy, contribute to significant ML advancements, and guide the future direction of ML systems at scale.

🎯 Requirements

• 7+ years of experience building and maintaining large-scale production ML systems, with a focus on performance, scalability, and reliability. • Proven experience as the owner or significant contributor to products used by tens of thousands of customers, with the ability to make complex design decisions. • Expertise in machine learning algorithms, productionizing ML models, and scaling systems to handle large data volumes. • Strong problem-solving skills with creative approaches to overcoming technical challenges. • Experience leading technical discussions, driving decisions, and setting technical standards for a team. • Excellent written and verbal communication skills, with the ability to articulate complex technical topics to both technical and non-technical stakeholders. • Familiarity with modern orchestration platforms (Kubernetes, containerization, microservice design) and distributed systems. • Ability to identify, define, and segment complex research problems and drive innovative solutions that align with business and technical goals.