AI​/ML Engineer

Position: AI / ML Engineer

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…