# Member of Technical Staff

**Company:** [Fireworks AI](https://hotfix.jobs/companies/fireworks-ai)
**Location:** San Mateo, CA, New York, NY
**Role:** ML Engineering
**Salary:** $160k – $180k/yr
**Experience:** 0+ years
**Skills:** Machine Learning, LLMs, Generative AI, Python, Software Engineering, Model Fine-Tuning, Reinforcement Learning, Full-Stack Development, Cloud Infrastructure, Inference Serving, Model Evaluation, RAG, Ai Coding Harnesses
**Posted:** 2026-09-08

> Build, deploy, and optimize AI applications and machine learning models for customer use cases while contributing to an internal ML platform. This new graduate role requires a technical master’s degree, hands-on ML or LLM experience, and strong customer communication skills.

## Job Description

## Responsibilities
- Build and present AI technology demos and proof-of-concepts for customers.
- Design, develop, and deploy end-to-end AI-powered applications tailored to customer needs.
- Add features and resolve issues in the internal machine learning platform.
- Integrate and enable new machine learning models on the platform or in client environments.
- Improve the performance, efficiency, and scalability of deployed models and applications.

## Requirements
- Master's degree in Computer Science, Engineering, or a related technical field, completed within the last 12 months or expected before starting.
- Strong skills working with AI coding harnesses.
- Practical software engineering experience through internships, research projects, open-source contributions, or substantial personal projects.
- Hands-on experience building with large language models or other machine learning models.
- Strong interpersonal and communication skills, with interest in working directly with customers.
- Comfort with ambiguity and fast-moving environments.

## Nice-to-haves
- Experience fine-tuning models using supervised fine-tuning, reinforcement learning from human feedback, or reinforcement fine-tuning.
- Experience shipping a full-stack or agentic application end to end.
- Understanding of generative AI, machine learning principles, and cloud or enterprise infrastructure.
- Familiarity with inference serving, model evaluation, or retrieval-augmented generation systems.

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