Principal Machine Learning Engineer

Benefits

* Competitive salary Location

Remote to start, then becomes hybrid in Raleigh, NC (relocation required; candidates able to relocate at the start of the contract are preferred, though relocation may occur upon conversion to full-time).

Experience Level

Principal Level (10+ years of experience in machine learning/AI engineering).

Role Overview

We are seeking a Principal Machine Learning Engineer to architect, develop, and advise on end-to-end AI solutions leveraging large language models (LLMs), Retrieval-Augmented Generation (RAG), and agentic systems. This is a senior individual contributor role for someone who wants to remain highly technical rather than move into people management, while providing technical strategy and architectural guidance to a growing data science team. The ideal candidate has played a lead role in designing and establishing a new agentic RAG-based system, with demonstrated ownership of meaningful architectural and technical decisions — not simply a contributor within a larger team.

Key Responsibilities

AI Architecture & Solution Design

* Architect, develop, and advise on end-to-end AI solutions leveraging LLMs, RAG, agentic systems, and cloud-scale infrastructure. * Construct, study, and train algorithms that learn from complex, high-dimensionality data to uncover patterns for predictive models and applications. * Apply techniques such as random forests, deep learning, generative modeling, and neural network memory to improve NLP and machine perception algorithms.

Proof of Concept & Technology Evaluation

* Develop proofs of concept and initial implementations for new AI capabilities. * Evaluate and test-drive new frameworks and tools to inform technical direction.

Technical Strategy & Leadership

* Work closely with architects to guide teams on AI system design and best practices. * Provide technical strategy and stay current with industry standards in AI and machine learning. * Understand the full environment and systems end to end, ensuring production readiness. * Align AI system design with business and technical goals.

Required Qualifications

* Deep expertise in LLMs, RAG, and agentic systems. * Experience with Model Context Protocol (MCP) and vector databases. * Strong experience with cloud platforms (AWS, Azure, or GCP). * Strong Python development skills and AI architecture experience. * Experience with MLOps and software engineering best practices. * Strong data engineering skills. * Demonstrated experience designing, architecting, and implementing a new agentic RAG-based system, with evidence of meaningful architectural and technical decision-making (not solely as a contributor within a larger team). * Engineering experience beyond core data science, including microservices architecture and cloud computing.

Preferred Qualifications

* Experience with GoLang. * Experience working with unstructured data and document-heavy domains. * Experience supporting or mentoring less senior data scientists/engineers as a technical lead.

Core Skills & Attributes

* Strong technical depth with a preference for remaining hands-on rather than pursuing people management. * Proven ability to make and own architectural and technical decisions on complex AI systems. * Strong collaboration skills, particularly working closely with architects and cross-functional teams. * Comfortable evaluating and adopting emerging tools and frameworks. * Excellent communication skills for translating technical strategy across teams. * Strong end-to-end systems thinking across AI architecture and production environments.

This is a remote position.