2+ years of engineering or data science management experience overseeing 4+ direct reports.
4+ years of hands-on ML or GenAI engineering experience, including production systems.
Proficient in GenAI fundamentals such as LLM APIs and evaluation methodology.
Strong decision-making skills for ambiguous problems and weighing project options.
Expertise in critiquing dataset quality and its business impact.
Ability to connect product orientation with technical solutioning.
People-focused management style that emphasizes growth and coaching.
Solid foundation in Python and software engineering principles.
Responsibilities
Manage and develop a small team of AI software engineers through coaching and performance evaluations.
Contribute to the codebase and design systems while owning delivery tasks.
Implement LLM patterns to automate complex tasks requiring human judgment.
Develop GenAI-powered solutions for various NLP challenges.
Collaborate with PM and engineering teams to define project scope and priorities.
Translate business problems into technical tasks for the team.
Stay up-to-date with GenAI advancements and their practical applications.
Benefits
Inclusive and collaborative company culture promoting open communication.
Career growth support including mentorship and leadership training.
Volunteer time off with matching charitable donations.
Access to conferences and employee resource groups.
Full Job Description
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 unblocking
Stay deeply technical: contribute to the codebase, design GenAI systems, and own meaningful slices of delivery alongside your team
Apply agentic LLM patterns (tool use, multi-step reasoning, orchestration) to automate high-complexity tasks that previously required human judgment
Design and build GenAI-powered solutions for complex NLP tasks - NER, classification, information retrieval, summarization, and structured output generation
Partner closely with the team's PM and adjacent engineering teams to scope, prioritize, and ship
Translate ambiguous business problems into well-scoped technical work - and help your engineers learn to do the same
Stay current with the fast-moving GenAI landscape and translate new capabilities into practical team impact
Skills & Requirements
2+ 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 systems
Strong 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 them
Technical 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 maintainability
Data acumen: you can critically assess a dataset, spot distribution problems, and reason about how data quality affects downstream model and business outcomes
Product orientation: you engage with business context naturally, partner with PM as an equal, and translate ambiguous requirements into well-scoped technical solutions
A 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 work
Solid Python and software engineering fundamentals - clean, testable code, REST API design, debugging, and familiarity with CI/CD
A genuine habit of self-improvement - you follow the field actively, experiment with new models and tools, and bring what's relevant back to the team
Extra, nice to haves
Experience managing engineers working across both traditional ML and GenAI
Experience with agentic orchestration frameworks
Fine-tuning experience with modern techniques - especially applied to domain adaptation for NLP tasks
PyTorch or Hugging Face familiarity
Familiarity with LLM evaluation frameworks and a structured approach to measuring model quality
Inference optimization awareness - understanding latency/cost/accuracy tradeoffs for LLM solutions
Experience building and deploying robust machine learning APIs in cloud environments (AWS or GCP)
What We Offer
An inclusive and collaborative 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.
There is strength in numbers - We are the Numerati
About Numerator
Numerator is a market research company founded in 2018. The company provides a range of market research services, including consumer insights, brand tracking, and advertising effectiveness. Numerator's platform is designed to help companies make data-driven decisions by providing them with real-time insights into consumer behavior. The company is headquartered in Chicago, Illinois, and has additional offices in New York, San Francisco, and Ottawa.
