Tech Lead Manager, AI / Machine Learning

Numerator / Market Track, LLC; United States; On-site; USD 90,000 - 130,000; Full time

Benefits offered by this job

Inclusive company culture

Market competitive compensation

Volunteer time off

Career growth support

Wellness resources and flexible policies

Job summary

Numerator / Market Track, LLC is seeking an AI Software Engineer to join the Machine Learning team. This position involves building and deploying high-performance deep learning systems and collaborating closely with various teams. Candidates should have over 2 years of experience in deploying ML systems, strong knowledge of GenAI, and solid Python skills. The role offers an inclusive company culture, competitive compensation, and growth opportunities.

Qualifications

• 2+ years of experience building and deploying ML or GenAI systems in production.
• Strong practical knowledge of LLM APIs and data quality assessment.
• Solid Python and REST API design skills, familiar with CI/CD.

Responsibilities

• Apply LLM patterns to automate complex tasks.
• Design GenAI solutions for NLP tasks.
• Build and maintain production ML APIs.

Skills

Experience building and deploying ML or GenAI systems

Strong practical GenAI fundamentals

Data acumen

Product orientation

Solid Python and software engineering fundamentals

Self-improvement habits

Tools

PyTorch

Hugging Face

Job description

AI Software Engineer

Location: Remote - United States
Req#: 609409

Job Description

Numerator is looking for a passionate AI Software Engineer to join our growing Machine Learning team. This is a unique opportunity where you will work with an established platform that handles millions of requests and massive amounts of data. You will design, build, deploy, and support high-performance deep learning systems in a rapidly scaling environment.

As a member of our team, you will make an immediate impact by building out and expanding our technology platforms across several software products. This high growth role gives you the chance to drive decisions for projects from inception through production.

How You'll Spend Your Time

• 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
• Build and maintain production ML APIs and data pipelines that deliver model-driven automation and insight into Numerator's products at scale
• Work closely with MLOps engineers, product & engineering managers, and other teams, owning a large part of the process from problem understanding to shipping the solution
• Stay current with the fast-moving GenAI landscape and translate new capabilities into practical team impact

What You'll Bring to Numerator

• 2+ years of experience building and deploying ML or GenAI systems in production
• Strong practical GenAI fundamentals: LLM APIs, context engineering, RAG, tool/function calling, skills, agents and evaluation methodology — understand why these techniques work, not just how to call them
• Data acumen: can critically assess a dataset, spot distribution problems, and reason about how data quality affects downstream model and business outcomes
• Product orientation: engage with business context naturally, ask the right clarifying questions, and translate ambiguous requirements into well-scoped technical solutions
• Solid Python and software engineering fundamentals — clean, testable code, REST API design, debugging, and familiarity with CI/CD
• Genuine habit of self-improvement — follow the field actively, experiment with new models and tools, and bring what's relevant back to the team

Nice to Haves

• 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 production environments (ideally cloud-based environments such as AWS or GCP)

Benefits

• An inclusive and collaborative company culture – an open environment while working together to get things done and adapting to changing needs
• 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
• Additional wellness resources and flexible policies

About Numerator

Numerator is 2,000 employees strong. We embrace diversity and foster innovation through diverse experiences, ideas, and backgrounds.

Being part of the Numerati means we’ll take care of you! From Recharge Days, maximum flexibility policy, wellness resources for employees and their families, to development opportunities and more — we’re always finding ways to better support, celebrate, and accelerate our team.