MLOps Team

Nanit is moving families beyond overwhelm by transforming how parents understand their baby's early years. We combine advanced AI, real-world data from billions of sleep hours, and clinical expertise to deliver the clarity and confidence every parent deserves. Trusted by over one million families and backed by $125M in funding, we're building an entirely new category: predictive parenting intelligence.

Here, your work directly impacts millions of families. Our team of scientists, engineers, and parents is small but mighty - we share a mission to make early childhood easier, healthier, and more connected. If you want to work on technology that genuinely matters, join us.

As an MLOps Team Leader at Nanit, you will own our AI infrastructure and backend engineering efforts, leading a team at the intersection of systems design and machine learning to build the engineering systems that turn Deep Learning and Computer Vision research into reliable, scalable production features.

What You’ll Be Doing:

• Lead MLOps Engineering: Own the roadmap and execution for a team of backend and AI infrastructure/MLOps engineers, setting technical direction, removing blockers, and holding the bar on delivery quality.
• Build Production AI Systems: Design and implement production-grade, end-to-end AI solutions, including agentic workflows, that integrate Deep Learning models and Computer Vision algorithms into real Nanit features. Own the offline experimentation and validation layer, including POC environments that let the Algo team move from research to production confidently.
• Architect Data Platforms: Drive the design and implementation of scalable data platforms and pipelines that power Nanit's AI capabilities reliably and with an eye on cost and scale.
• Cross-functional Collaboration: Work closely with the Algorithms and Data teams to tackle complex, real-world problems, translating research into shippable, maintainable systems.
• Elevate Engineering Standards: Champion Software Engineering and System Design best practices across the group, introducing the right methodologies, tooling, and culture of craft.

Who You Are:

• Professional Experience: At least 5 years of hands-on Software Engineering experience, with a minimum of 2 years in a team lead or managerial role.
• Technical Proficiency:
  • Production Systems and DevOps: Proven experience building high-scale, production-grade systems on a cloud platform (AWS preferred), with solid command of DevOps practices including CI/CD, containerization, and observability.