Senior ML Engineer: Conversational AI & Production

Numa; United States; Remote; USD 142,000 - 177,000; Full time

Benefits offered by this job

Equity Packages

Flexible PTO

Fully Covered Group Insurance

Job summary

Numa is building AI-native dealership automation to power service and sales with advanced AI agents. The Senior Machine Learning Engineer will ship ML/LLM powered systems that interact with customers thousands of times daily, including voice agents that book service appointments and route calls through natural conversations.

You will work across products, ship AI features, and contribute to the ML platform with model serving, LLM infrastructure, and production observability.

Qualifications

• 6+ years of software or ML engineering experience.
• Strong Python and solid software engineering fundamentals.
• Hands-on experience building AI systems; training and deploying ML models.
• Experience with LLMs: prompting, tools, retrieval.
• Evaluation-first mindset to measure improvements.
• Comfort operating with ambiguity in a product environment.
• Ownership and clear communication from problem framing to shipped results.

Responsibilities

• Build conversational AI systems for phone and SMS.
• Develop tooling: memory, knowledge graphs, and customization for agents.
• Train, evaluate, and deploy ML models using Ray Serve and Dagster.
• Create offline and online evaluations, simulations, and CI gates.
• Implement shared evaluation, observability, and LLM tooling for faster shipping.
• Contribute to design reviews, technical writing, and mentorship.
• Work autonomously when goals are clear and help create clarity when not.

Skills

Python

ML engineering

LLMs

Evaluation-first approach

Ownership & communication

Tools

LiveKit

Ray Serve

Dagster

Vertex AI

Kubernetes

GCP

Pulumi

OpenAI API

Job description

Numa is building AI-native dealership automation to power service and sales with advanced AI agents. The Senior Machine Learning Engineer will ship ML/LLM powered systems that interact with customers thousands of times daily, including voice agents that book service appointments and route calls through natural conversations.

You will work across products, ship AI features, and contribute to the ML platform with model serving, LLM infrastructure, and production observability.