Director, AI & Data Science

LRN Corporation

1d•Remote

About The Position

The Director of AI & Data Science will define and lead the company’s applied AI strategy, delivering scalable ML and LLM-powered solutions that drive measurable business impact. This role partners closely with Product, Engineering, Security/Compliance, Sales, and Marketing to translate customer needs into production-ready AI capabilities. This is a hands-on leadership role requiring both technical depth and organizational influence. You will coach and grow a small team, architect end-to-end AI systems, and help the company communicate AI value credibly and responsibly to customers and stakeholders.

Requirements

Proven ability to lead an applied AI team (player-coach) and drive delivery in a production environment
Strong end-to-end ML/AI engineering judgment: data, modeling, evaluation, deployment, monitoring, iteration
Practical experience with LLMs and modern AI tooling, including prompt/system design, retrieval (RAG), fine-tuning (when appropriate), and evaluation
Ability to translate ambiguous business problems into tractable AI work with clear scope, milestones, and measurable outcomes
Excellent communication: can explain complex trade-offs to technical and non-technical audiences
Experience collaborating with Sales/Marketing on customer-facing AI positioning and solutioning
PhD Plus 2 years industry experience/ Masters plus 4 years / bachelor's plus 6 years industry experience
Field of study computer science or at least 3 years as a software developer
Strong Python and modern ML stack (e.g., PyTorch / sklearn; data tooling; experimentation, vector databases)
Understanding of modern software development and technology practices like git, APIs, containerization, CI/CD
Experience with model evaluation, guardrails, observability
Understanding of responsible AI: privacy, security, governance, and risk controls—especially in regulated/enterprise contexts

Nice To Haves

Node.js and other backend development skills
Experience in B2B SaaS, compliance/ethics, risk, or enterprise workflows
Experience designing evaluation frameworks for LLM features (quality, hallucination risk, latency/cost trade-offs)
Prior customer-facing technical leadership (pre-sales, workshops, exec briefings)

Responsibilities

Lead and grow the AI & DS function: manage/mentor a team of ML/data scientists and guide hiring, prioritization, and delivery
Set technical strategy and standards: choose architecture, tooling, evaluation methods, and deployment patterns (MLOps / LLMOps), with a strong focus on reliability and risk management
Build and ship AI capabilities: deliver end-to-end solutions (problem framing → data → modeling → evaluation → deployment → monitoring)
Partner cross-functionally: collaborate with Product/Engineering to integrate AI into workflows and product experiences; align with Security/Privacy/Legal for responsible use
Enable GTM: support Sales and Marketing with AI narratives, customer-facing discussions, solutioning, and (when needed) technical validation
Measure impact: define success metrics, run experiments, and communicate trade-offs and results clearly to execs and stakeholders