Anam Our mission is to humanise technology. We're developing real-time, emotive AI humans who you can converse with at any time, in any language. They communicate through verbal and nonverbal cues, are photorealistic and have low response latency. Try our demo here.

Where you come in We need a hands-on MLOps engineer who isn't afraid to dive deep into every aspect of the ML lifecycle. You'll be the bridge between our research and production environments, handling everything from data preparation to production deployment. Your role will span building robust data curation pipelines, automating training workflows, and scaling our inference infrastructure. This includes implementing data quality checks, designing efficient storage solutions for our large training datasets, and ensuring our models perform reliably at scale. You'll work closely with our research team to streamline the path from experimentation to production, and collaborate with backend engineers to optimize our cloud infrastructure. As an early hire, you'll help establish our MLOps practices and won't shy away from rolling up your sleeves to solve complex problems as they arise.

You have

• Strong cloud infrastructure experience with a DevOps mindset
• Experience in data pipeline design and processing at scale
• Production ML deployment experience
• [Bonus] Experience with real-time inference systems
• [Bonus] Early-stage startup experience

You will gain

• The opportunity to build data infrastructure for cutting-edge AI technology
• Experience working with best-in-class engineers & researchers
• A competitive salary, reviewed regularly
• Generous equity, coming in as an early employee
• The opportunity to grow into a leadership role

If this sounds exciting, we'd love to hear from you - [email protected].