At LTV.ai, we’re redefining customer engagement for e-commerce brands by empowering them with their own AI-powered ambassadors to deliver hyper-personalized Email and SMS interactions at an unprecedented scale.
Our platform enables brands to communicate with their audience in a natural and contextually relevant manner, driving higher engagement and conversion rates. While increasing LTV and driving measurable growth, we help brands stay focused on what matters most - the customer.
We’re a fast-moving team building a high-growth company that’s transforming the e-commerce industry. As an early team member, you’ll play a key role in shaping both our product and the future of e-commerce, with the opportunity to grow alongside us.
Role Responsibilities:As a Senior AI / ML Engineer, you’ll be an individual contributor focused on leveling up our AI/ML product experiences and infrastructure. You’ll take core systems from V1 to V2 and beyond - with an emphasis on performance, reliability, and ML-driven value creation for our customers.
Your scope will include:
Evolving our segmentation engine to enable more precise, adaptive audience creation using behavioral, conversational and transactional data.
Improving our product recommendation engine to deliver real-time, context-aware suggestions across messaging channels.
Enhancing our personalization engine to dynamically tailor content and offers at scale, with deeper user modeling.
Strengthening AI infrastructure to ensure system reliability, latency improvements, and better orchestration of multi-model pipelines.
Partnering with Product and Engineering to embed ML best practices across our platform, from training workflows to model deployment.
Contributing to architectural decisions, experimenting with new approaches (e.g., Retrieval Augmented Generation, vector search), and helping scale our infrastructure intelligently.
2 - 3+ years of experience building AI/ML-powered products or infrastructure at scale.
Strong understanding of supervised learning, ranking systems, and personalization strategies.
Hands-on experience with tools like PyTorch, TensorFlow, Hugging Face, or similar ML libraries.
Familiarity with real-time or batch data pipelines, and deploying models in production.
Comfortable optimizing across performance, cost, and user impact.
Bonus: Experience in e-commerce, recommendation systems, or LLM-driven workflows.
Frontend: React (TypeScript)
Backend: NestJS (TypeScript)
Infrastructure: AWS, managed with Terraform
Databases: PostgreSQL, ClickHouse
ML/AI: Python, Hugging Face, custom pipelines leveraging multiple LLMs
Launched a personalization engine that scales to 40M+ users with 10% MoM growth.
Built multi-model orchestration to optimize LLM interactions for cost and accuracy.
Partnered with major e-commerce brands like Fabletics and Sur La Table to deliver personalized marketing at scale.
Deeper segmentation and dynamic user memory
Agentic AI workflows for continuous interaction optimization at an individual and brand level
Embedding-based personalization at the message level
Real-time model switching and routing infrastructure
Base depends a lot on the person but we reward A players
Equity included
If you’re curious, ambitious, and hungry to build something big, feel free to email our founder directly [email protected] - we’d love to hear from you.
