2+ years of experience in building and deploying ML or GenAI systems in production.
Strong understanding of GenAI fundamentals including LLM APIs and context engineering.
Proven data assessment skills for spotting distribution problems and data quality implications.
Ability to engage productively with business contexts and translate requirements into technical solutions.
Solid foundation in Python and software engineering best practices.
Responsibilities
Apply agentic LLM patterns to automate complex tasks historically handled by humans.
Design and implement GenAI-powered solutions for various NLP tasks like classification and summarization.
Develop and maintain ML APIs and data pipelines for model-driven automation across products.
Collaborate with MLOps and product teams throughout the problem-solving and deployment process.
Stay updated on the GenAI landscape and integrate new capabilities into team operations.
Benefits
Inclusive and collaborative company culture with an open environment.
Volunteer time off and charitable donation matching.
Strong support for career growth through mentorship and training.
Opportunities to attend conferences and engage with 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.
