Staff AI / ML Engineer

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We’re a remote-first workforce with collaborative work spaces in San Francisco and Kitchener, Ontario, and employees in several U.S. states. If you’re interested in joining a dynamic, culture-driving company—where learning invaluable skills is all in a day’s work—we invite you to apply.

• →Design and build agentic AI systems that power consumer learning products, including multi-step reasoning, tool use, and orchestration architectures.
• →Select and integrate foundation models (LLMs, multimodal) based on product requirements, making pragmatic trade-offs between quality, latency, cost, and safety.
• →Build evaluation and observability frameworks that ensure AI product quality at scale, including automated testing, human-in-the-loop review, and production monitoring.
• →Architect reliable, production-grade AI pipelines, including prompt management, context retrieval (RAG), caching, and fallback strategies.
• →Collaborate with Product, Design, and Engineering to translate ambiguous product goals into well-defined technical approaches and ship features end-to-end.
• →Stay deeply current with the foundation model landscape—new models, techniques, agentic frameworks, and research—and bring that knowledge to bear on product decisions.
• →Mentor and elevate the AI engineering team by sharing best practices, leading design reviews, and establishing reusable patterns for agentic product development.

• 7+ years of software engineering experience, with 3+ years focused on building products with large language models or foundation models.
• Demonstrated experience shipping consumer-facing AI products that use agentic patterns (tool use, multi-step reasoning, orchestration, planning).
• Deep working knowledge of the current foundation model ecosystem: model providers (OpenAI, Anthropic, Google, open-source), prompt engineering, RAG architectures, evaluation frameworks, and orchestration tooling.
• Strong software engineering fundamentals: system design, API design, production observability, and the ability to write clean, maintainable code in Python.
• Track record of staying on the cutting edge—you can point to specific ways you’ve incorporated new research, models, or techniques into shipped products.
• Excellent collaboration and communication skills; experience working cross-functionally with product, design, and engineering teams.

• Experience with model fine-tuning or distillation (SFT, DPO, RLHF).
• Background in edtech, consumer media, or content platforms.
• Published research or open-source contributions in AI/ML.
• Experience with multi-agent system design or advanced orchestration frameworks.