AI / ML Engineer

Harnham; Houston (TX); Híbrido; USD 162.000 - 198.000; Jornada completa

Descripción de la vacante

Harnham in Houston, TX, is hiring a Senior AI / Machine Learning Engineer for a hybrid role with four days onsite weekly. The position targets experts in traditional ML/NLP and recent Generative AI, including RAG pipelines and agentic AI systems. You will own design, development, and deployment of AI solutions in production.

You will work across LLM-powered apps, retrieval systems, and document processing workflows, driving real-world impact with advanced ML engineering practices.

Formación

• 5+ years of hands-on ML engineering experience.
• Strong NLP foundation, transformer architectures.
• Production ML deployment ownership.
• Strong Python experience.
• Hands-on Generative AI and LLM experience.
• Experience with RAG and embeddings.
• Agentic AI system design and deployment.
• Progression from traditional ML/NLP to Generative AI and Agentic AI.

Responsabilidades

• Design, develop, and deploy production-grade ML, Generative AI, and Agentic AI systems.
• Architect and implement AI agents capable of reasoning through tasks and automating workflows.
• Build and optimize RAG pipelines and embedding-based retrieval systems.
• Apply NLP and transformer expertise to unstructured text problems.
• Develop and maintain Python-based ML pipelines and deployment workflows.
• Deploy ML models and LLM-based systems into production environments.
• Evaluate and improve model performance and retrieval quality.
• Contribute to technical design decisions for AI solutions.
• Apply ML expertise to document processing and workflow automation.

Descripción del empleo

Work Arrangement: Hybrid, 4 days onsite per week

Base Salary: Up to $180,000 + 15% annual bonus

Work Authorization: To be confirmed

About the Company

We are partnering with an established organization investing in advanced Artificial Intelligence and Machine Learning capabilities to support business operations, automate complex workflows, and develop production-ready AI solutions.

The organization is expanding its AI capabilities with a focus on Generative AI, Large Language Models (LLMs), and Agentic AI systems. This opportunity is part of that initiative, bringing deeper Machine Learning Engineering expertise into the development and deployment of advanced AI solutions.

About the Role

We are seeking a Senior AI / Machine Learning Engineer with a strong foundation in traditional Machine Learning, particularly Natural Language Processing (NLP), transformer architectures, and production model deployment, who has more recently transitioned into Generative AI and Agentic AI engineering.

This is a hands-on engineering position for someone who understands the underlying ML technologies behind modern AI systems and has experience taking models and AI applications from development into production.

The ideal candidate brings a combination of established ML engineering expertise and recent experience designing and deploying RAG pipelines, LLM-powered applications, and agentic systems.

You will serve as a key technical contributor and AI subject matter expert, helping shape how advanced AI capabilities are designed, engineered, and deployed across the organization.

This is an ML Engineering-focused role, not a traditional Data Science, analytics, or general software development position.

What You'll Do

• Design, develop, and deploy production-grade Machine Learning, Generative AI, and Agentic AI systems.
• Architect and implement AI agents capable of reasoning through tasks, interacting with tools, retrieving information, and automating complex workflows.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines, embedding-based retrieval systems, and LLM-powered solutions.
• Apply expertise in NLP, transformer architectures, and language models to solve problems involving unstructured text and document data.
• Develop and maintain Python-based ML pipelines and model deployment workflows.
• Take ownership of deploying ML models and LLM-based systems into production environments.
• Evaluate and improve model performance, retrieval quality, and overall AI system effectiveness.
• Contribute to technical design decisions and help establish effective approaches for developing and deploying AI solutions.
• Apply Machine Learning expertise to practical business problems involving document processing, language understanding, and workflow automation.

What We're Looking For

• 5+ years of hands-on Machine Learning Engineering experience, ideally 7+ years, with a strong emphasis on building and deploying ML systems rather than primarily performing Data Science or analytics.
• Strong traditional NLP and Machine Learning foundation, including experience with transformer architectures, text processing, and models designed to work with unstructured language data.
• Production ML deployment experience, with demonstrated ownership of moving Machine Learning models from development into real-world production environments.
• Strong Python experience developing Machine Learning models, pipelines, and AI systems.
• Hands-on Generative AI and LLM experience, including the development and deployment of LLM-powered solutions in production.
• Experience with RAG and embeddings, including building retrieval pipelines and working with embedding-based search and information retrieval.
• Agentic AI system design and deployment, with experience building and deploying AI agents or agentic workflows in production.
• A demonstrated progression from traditional ML/NLP engineering into modern Generative AI and Agentic AI development.

Nice to Have

• Experience fine-tuning pretrained Machine Learning models or Large Language Models for specialized use cases.
• Approximately 10+ years of overall professional experience, although candidates with fewer years and exceptional hands-on ML Engineering expertise will be considered.
• Additional experience building AI solutions for document processing, unstructured data extraction, or complex workflow automation.

Why This Role?

This opportunity is particularly well suited for an experienced Machine Learning Engineer looking to apply both traditional ML expertise and modern Generative AI capabilities in a role with meaningful technical ownership.

• Technical ownership: Play a central role in designing and deploying advanced AI systems rather than focusing exclusively on experimentation or prototypes.
• Modern AI development: Work directly with LLMs, RAG, embeddings, and agentic architectures while leveraging deeper traditional ML expertise.
• High-impact position: Serve as a key AI technical resource, contributing to system design decisions and production implementation.
• Real-world applications: Build AI solutions that address practical business challenges, including language understanding, document processing, and workflow automation.
• Continued technical growth: Apply established ML engineering knowledge to increasingly sophisticated Generative AI and autonomous agent systems.

Location & Schedule

This position is based in Houston, Texas, with an expectation of working onsite four days per week. There is some flexibility regarding office location within the Houston area.

Compensation & Relocation

• Base salary: Up to $180,000 annually
• Annual performance bonus: 15%
• Target annual cash compensation: Up to $207,000, assuming full bonus payout
• Relocation assistance: Up to $10,000, structured as a sign-on bonus