Note: The job is a remote job and is open to candidates in USA. Numerator is reinventing the market research industry by providing unmatched insights into consumer behavior. They are looking for a hands-on Tech Lead Manager to lead their Machine Learning team, responsible for managing engineers while also contributing technically to the development of GenAI features and solutions.
Responsibilities
- 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
- 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
- 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)
Benefits
- 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.
Company Overview
Company H1B Sponsorship