Senior Machine Learning Engineer- LLMs & Self-Hosted AI

Navan

Quick summary

Work type: On-site
Location: Redwood City, CA
Posted: 56 days ago
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $210k

$161k most similar roles pay here $272k

This listing doesn't post a salary. Most similar roles pay $174,612–$246,150.

Based on 240 similar postings.

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About Navan

Navan (formerly TripActions) is a travel and expense management platform that provides corporate travel booking, expense management, and card solutions to simplify business travel for enterprises. Industry: Travel Management & Financial Technology

Navan currently has 20 open roles on FindRole.

Listed pay typically runs $113,400–$252,000 across 7 roles with salary data.

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At a glance

TL;DR · Senior Machine Learning Engineer- LLMs & Self-Hosted AI

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As a Senior ML Engineer at our innovative tech company, you will join a dynamic team focused on developing an advanced agentic support chatbot. Your primary responsibilities include fine-tuning high-performance models for specific domain tasks and tool-calling execution, enhancing the chatbot’s agentic capabilities to ensure reliable interactions with various LLMs and SLMs, optimizing inference processes using vLLM, and creating robust evaluation frameworks to measure model performance. You will work extensively with PyTorch and the Hugging Face ecosystem, possess strong data engineering skills, and be proficient in AI-assisted development workflows. Additionally, expertise in fine-tuning strategies such as SFT, RLHF, and DPO is essential, along with experience in containerization, orchestration, model quantization, and API development using FastAPI. This role involves tackling complex business challenges through cutting-edge machine learning techniques on a large scale.

Skills

PyTorch Hugging Face Agentic systems Fine-tuning strategies Ray Model quantization FastAPI DVC Weights & Biases MLflow CI/CD Python

What you'll do

Design and execute fine-tuning strategies to enhance model accuracy on specific tasks.
Develop agentic capabilities for the chatbot, ensuring reliable tool use and interactions.
Deploy and manage large-scale models using high-performance inference engines like vLLM.
Build comprehensive evaluation frameworks to measure model performance and business impact.
Expertise in fine-tuning strategies such as SFT, RLHF, DPO, and parameter-efficient techniques.

What we're looking for

Deep experience with PyTorch and Hugging Face ecosystem.
Strong skills in data engineering, synthetic data generation, and active learning.
Expertise in fine-tuning strategies for LLMs and parameter-efficient techniques.
Proficiency in building agentic systems including ReAct and function calling.
Experience with AI-assisted development workflows to accelerate project timelines.

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