Define and own Platzi's AI roadmap from infrastructure and tooling to features that directly impact the learner experience
Design, develop, and deploy machine learning models, LLM-powered features, and AI-driven pipelines at production scale
Translate ambiguous product and business needs into concrete technical solutions, working closely with Product, Engineering, and Data teams
Evaluate, prototype, and integrate emerging AI technologies including foundation models, RAG architectures, and agentic frameworks with a bias toward what ships over what's theoretically elegant
Establish engineering practices for model evaluation, monitoring, responsible AI use, and MLOps across the organization
Mentor engineers and grow a team with strong technical judgment and a culture of rapid, deliberate experimentation
Stay ahead of the AI research landscape and identify what's worth applying to real-world problems today not in 18 months
Communicate AI strategy and technical decisions clearly to non-technical stakeholders, including leadership and external partners

Requirements

7+ years of experience in machine learning, applied AI, or related fields, with at least 2 years in a technical leadership or staff-level role
Deep hands-on expertise in modern ML frameworks (PyTorch, TensorFlow, or JAX) and the LLM ecosystem — fine-tuning, RAG, prompt engineering, vector databases, and agentic frameworks
Proven track record of building and deploying AI/ML systems in production environments at scale, not just proof of concepts
Strong understanding of NLP, deep learning architectures, and retrieval-augmented generation
Experience designing MLOps pipelines: model versioning, A/B testing, monitoring, and retraining workflows
Ability to lead and grow technical teams without defaulting to process overhead — you align people through clarity and shared technical judgment
Strong communication skills; you can explain a model's tradeoffs to an engineer and its business impact to a CEO in the same afternoon
Nice to have: experience applying AI in education, content generation, or personalization systems; open-source contributions or published research

Benefits

Hardware — Laptop, smartphone, and ergonomic workstation fully provided
Books — Unlimited professional books via Kindle (device included)
Parental Leave — Extended maternity and paternity leave
Equity — Option pool participation available to all team members
PTO — 15 days of paid vacation per year from day one
Team Syncs — In-person team gatherings throughout the year
Villa Platzi — Annual full-company retreat somewhere in the world

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningapplied AImodern ML frameworksPyTorchTensorFlowJAXNLPdeep learning architecturesMLOpsretrieval-augmented generation

Soft Skills

technical leadershipmentoringcommunicationteam alignmentclarityshared technical judgmentrapid experimentationdecision-makingproblem-solvingstakeholder engagement