Senior Machine Learning Engineer

Rise Technical; United States; On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Equity

PTO

Job summary

Rise Technical is seeking a Senior ML Engineer in the United States to own autonomous multi-agent architectures within a high-growth cybersecurity AI startup. You will design, implement, and optimize production-grade LLM systems and agent orchestration in a fast-moving environment.

The role involves contributing to model fine-tuning, data curation, and scalable deployment, working closely with leadership and cross-functional teams to push state-of-the-art autonomous security solutions into

Qualifications

• Experience building production ML systems with LLM-powered agents.
• Strong Python programming with PyTorch and Hugging Face.
• Experience shipping multi-agent or tool-using LLM systems to production.

Responsibilities

• Design and improve multi-agent architectures, planning loops, and tool-use.
• Contribute to model training via data curation, supervised fine-tuning, and preference optimization.
• Build evaluation harnesses to track model and agent performance.
• Deploy and scale production agents within Kubernetes environments.

Skills

Production ML

LLMs

Python

PyTorch

Hugging Face

Tools

vLLM

TensorRT-LLM

Kubernetes

Job description

$150,000 -$230,000 + Equity + PTO

Are you a Senior ML Engineer with experience building production-grade LLM systems looking to take ownership of autonomous, multi-agent architectures within a high-growth cybersecurity AI start-up?

This is an opportunity to join a fast-growing AI company developing next-generation autonomous offensive security platforms. You will join a specialized AI engineering team and play a critical role in advancing their flagship platform, moving the needle on complex problems like exploit chaining, multimodal vision, and co-evolutionary self-training loops.

In this role, you will design, implement, and optimize highly sophisticated multi-agent architecture, while contributing directly to model fine-tuning and production scalability. Working closely with engineering leadership and cross-functional teams, you will transition advanced multi-agent systems from cutting-edge experimentation into robust, production-ready enterprise solutions.

This role would suit an ML Engineer who enjoys solving deep, technical agent-orchestration challenges and wants to be a foundational builder of autonomous, self-improving security systems.

The Role:

• Design and improve multi-agent architectures, planning loops, and tool-use
• Contribute to model training via data curation, Supervised Fine-Tuning, and preference optimization (DPO/GRPO)
• Build evaluation harnesses to track model and agent performance
• Optimize inference for latency and throughput using vLLM or TensorRT-LLM
• Deploy and scale production agents within Kubernetes environments

The Person:

• Experience building production ML systems, with a strong focus on LLMs or LLM-powered agents
• Strong Python programming alongside PyTorch and Hugging Face
• Experience with Supervised Fine-Tuning, preference optimization, and synthetic data generation
• Experience shipping multi-agent or tool-using LLM systems to production