Senior AI/ML Engineer - GenAI & MLOps (Remote)

Geomatik; Houston (TX); On-site; USD 120,000 - 190,000; Part time

Job summary

Octave is seeking an AI/ML Engineer to build reliable, scalable systems for Generative AI and Agentic AI features, and to deploy data-driven solutions for our document-based compliance management platform.

You will design and deploy end-to-end MLOps pipelines, integrate LLM evaluation frameworks, monitor models in production, and collaborate with cross-functional teams to translate business needs into practical AI solutions for regulated environments.

Qualifications

• 5+ years in data science, ML engineering or related roles.
• 3+ years building NLP/generative AI applications in production.
• Track record deploying ML systems with monitoring and governance.
• Bachelor's or Master's in Data Science, CS, Statistics.

Responsibilities

• Build and deploy Generative AI features using foundation models and inference pipelines.
• Design agentic AI systems for compliance workflows, document review, regulatory mapping and multi-step reasoning.
• Integrate comprehensive LLM evaluation frameworks with development and production systems.
• Build and operate end-to-end MLOps pipelines, deployment systems, monitoring and rollbacks workflows.
• Implement explainability frameworks (SHAP/LIME) and monitoring dashboards ensuring transparency.
• Collaborate with cross-functional teams to translate business needs into ML solutions and communicate insights to stakeholders.

Skills

Python

ML & NLP

Generative AI

LLMs

MLOps

AWS SageMaker

Prompt Engineering

Data Visualization

Communication

Education

Bachelor's or Master's in CS/DS

Tools

Docker

Kubernetes

Spark

Databricks

Snowflake

LangChain

Job description

Octave is seeking an AI/ML Engineer to build reliable, scalable systems for Generative AI and Agentic AI features, and to deploy data-driven solutions for our document-based compliance management platform.

You will design and deploy end-to-end MLOps pipelines, integrate LLM evaluation frameworks, monitor models in production, and collaborate with cross-functional teams to translate business needs into practical AI solutions for regulated environments.