Senior ML Ops 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

• Maintain, extend, and improve existing data/ML workflows, and implement new ones to handle high-velocity data. • Provide interfaces and systems that enable ML engineers and researchers to build datasets on demand. • Influence data storage and processing strategies. • Collaborate with the ML team, as well as frontend and backend teams, to build out our data platform. • Reduce time-to-deployment for dashboards and ML models. • Establish best practices and develop pipelines and software that enable ML engineers and researchers to efficiently build and use datasets. • Work with large datasets under performance constraints comparable to those at the largest companies. • Iterate quickly, with a focus on shipping early and often, ensuring that new products or features can be deployed to millions of users.

🎯 Requirements

• Minimum of 3 years of experience in a data role involving designing and building data stores, feature engineering, and building reliable data pipelines that handle high loads. • At least 2 years of professional software development experience in a role other than data engineering. • Proficiency in Python and experience working with Kafka infrastructure and distributed data systems. • Deep understanding of SQL and NoSQL databases (preferably Clickhouse). • Familiarity with public cloud providers (AWS or Azure). • Experience with CI/CD and orchestration platforms: Kubernetes, containerization, and microservice design. • Proven ability to make independent decisions regarding data processing strategy and architecture. • Thoughtful, self-directed individual who is able to operate effectively in a fast-paced environment. • Nice to Have: • Experience collaborating across ML, backend, and frontend teams. • Understanding of machine learning fundamentals, including model training, inference, and frameworks such as PyTorch or TensorFlow.