What are the responsibilities and job description for the Senior AI / ML Engineer position at LTV.ai?
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.
Why join us?
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:
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.
Why join us?
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