Machine Learning Implementation Engineer

Overview

I’m working with a fast-growing AI startup building AI-powered Virtual Agents that automate complex operational workflows directly inside customer systems. Their platform is helping businesses deploy practical AI quickly - without heavy integrations, long onboarding cycles, or major process changes.

Backed by leading AI investors and already working with major customers across insurance, healthcare, and marketplaces, they’re now hiring ML Implementation Engineers to help scale deployments and customer impact.

Why this role stands out

• Blend of software engineering, ML systems, and customer-facing work
• High ownership with direct real-world impact
• Build and deploy practical AI products, not just prototypes
• Work across infrastructure, deployment, MLOps, and AI services
• Fast-moving environment with strong product influence
• Work directly with customers to automate workflows using AI agents
• Deploy AI solutions into real operational environments
• Improve reliability, observability, and deployment infrastructure
• Contribute to the core AI agent platform and tooling
• Help shape how ML and computer vision systems are implemented at scale
• Strong software engineering fundamentals
• Exposure to ML systems, infrastructure, deployment, or MLOps
• Comfortable solving ambiguous problems with customers
• Engineers who enjoy ownership, fast iteration, and practical AI deployment
• You don’t need experience across every area to be a fit. The team is open to engineers from a range of backgrounds who enjoy building useful AI systems and working closely with customers.