We’re reinventing the market research industry. Let’s reinvent it together.At Numerator, we believe tomorrow’s success starts with today’s market intelligence. We empower the world’s leading brands and retailers with unmatched insights into consumer behavior and the influencers that drive it.Numerator is looking for a hands‑on Tech Lead Manager to join our growing Machine Learning team. This is a 50/50 player‑coach role: you'll directly manage a small team of ML engineers while continuing to write code, design systems, and ship GenAI features yourself. You'll work with an established and rapidly evolving platform that handles millions of requests and massive data volumes, and you'll be responsible for both the team's technical direction and the growth of the people on it.Historically, our team has focused on reducing COGS through ML automation. That work continues — and we're now also building agentic experiences for clients and internal stakeholders. You'll help shape both the technical roadmap and how the team operates as we expand into this space.How You’ll Spend Your Time:Manage and grow a small team of AI software engineers — 1:1s, career development, performance, hiring, and day‑to‑day unblockingStay deeply technical: contribute to the codebase, design GenAI systems, and own meaningful slices of delivery alongside your teamApply agentic LLM patterns (tool use, multi‑step reasoning, orchestration) to automate high‑complexity tasks that previously required human judgmentDesign and build GenAI‑powered solutions for complex NLP tasks — NER, classification, information retrieval, summarization,



and structured output generationPartner closely with the team's PM and adjacent engineering teams to scope, prioritize, and shipTranslate ambiguous business problems into well‑scoped technical work — and help your engineers learn to do the sameStay current with the fast‑moving GenAI landscape and translate new capabilities into practical team impactWhat You’ll Bring to Numerator2+ years of engineering or data science management experience — 4+ direct reports, performance conversations, hiring.4+ years of hands‑on ML or GenAI engineering experience, including production systemsStrong practical GenAI fundamentals: LLM APIs, context engineering, RAG, tool/function calling, agents, and evaluation methodology — you understand why these techniques work, not just how to call themTechnical judgment: you can scope ambiguous problems, make sound build-vs-buy and custom-vs-off-the-shelf calls, and balance shipping speed with long‑term maintainabilityData acumen: you can critically assess a dataset, spot distribution problems, and reason about how data quality affects downstream model and business outcomesProduct orientation: you engage with business context naturally, partner with PM as an equal,



and translate ambiguous requirements into well‑scoped technical solutionsA people‑first management style: you grow engineers through coaching and stretch work, give direct and timely feedback, and create the conditions for your team to do their best workSolid Python and software engineering fundamentals — clean, testable code, REST API design, debugging, and familiarity with CI/CDA genuine habit of self‑improvement — you follow the field actively, experiment with new models and tools, and bring what's relevant back to the teamExtra, nice to havesExperience managing engineers working across both traditional ML and GenAIExperience with agentic orchestration frameworksFine‑tuning experience with modern techniques — especially applied to domain adaptation for NLP tasksPyTorch or Hugging Face familiarityFamiliarity with LLM evaluation frameworks and a structured approach to measuring model qualityInference optimization awareness — understanding latency/cost/accuracy tradeoffs for LLM solutionsExperience building and deploying robust machine learning APIs in cloud environments (AWS or GCP)What We OfferAn inclusive and team-oriented company culture- we work in an open environment while working together to get things done, and adapt to the changing needs as they come.Market competitive total compensation package.Volunteer time off and charitable donation matching.Strong support for career growth, including mentorship programs, leadership training, access to conferences and employee resource groups.#J-18808-Ljbffr

📌 Tech Lead Manager, Ai / Machine Learning (Toronto)
🏢 Numerator
📍 Toronto