Applied AI/ML Engineer / Data Scientist

Vertage is building NextBrain, and this Applied AI/ML Engineer / Data Scientist role focuses on turning AI capabilities into reliable, production-deployed intelligence. The work spans applied data science, machine learning, generative AI, and software engineering, with an emphasis on rigorous evaluation and measurable model behavior.

What you will do

• Design, develop, evaluate, and deploy AI/ML capabilities within NextBrain.
• Build analytical models for use cases including anomaly detection, asset health, forecasting, classification, and other operational scenarios.
• Develop generative AI and agentic capabilities using enterprise-approved foundation models and AI platforms.
• Create prompts, tools, agents, workflows, and orchestration patterns for NextBrain.
• Implement Retrieval-Augmented Generation (RAG) and knowledge-retrieval solutions when appropriate.
• Develop evaluation frameworks for LLM and agent behavior.
• Define metrics for accuracy, relevance, reliability, hallucination, latency, and cost.
• Set up guardrails and validation mechanisms for AI-generated responses.
• Collaborate with Data Engineering to define training, inference, retrieval, and feature-data requirements.
• Partner with the Full Stack/Cloud Engineer to deploy AI services into production.
• Prototype quickly while designing solutions that can transition into production.
• Monitor model and agent performance and continuously improve deployed capabilities.
• Communicate model behavior and analytical findings to engineers, product stakeholders, and operational subject-matter experts.
• Stay current with emerging AI, agentic AI, ML, and data-science technologies and assess their applicability to NextBrain.

Skills and qualifications

• Master's degree or Bachelor's degree with equivalent experience in Computer Science, Data Science, Engineering, Statistics, Machine Learning, or a related discipline.
• 4+ years of experience developing machine-learning or advanced analytics solutions.
• Strong Python skills.
• Experience with common ML and data-science frameworks and libraries.
• Experience taking analytical or ML solutions from experimentation into production.
• Strong foundation in statistics, experimentation, model evaluation, and data analysis.
• Experience working with cloud-based data and compute environments.
• Experience with APIs, software-development practices, source control, and CI/CD.
• Demonstrated ability to translate business or operational problems into analytical approaches.

Technologies you will work with

• Python
• Language models
• Retrieval-Augmented Generation
• LLM
• APIs
• CI/CD

Preferred experience

• Hands-on experience developing applications using LLMs.
• Experience with agentic frameworks, tool calling, MCP, or similar AI orchestration technologies.
• Experience with RAG, embeddings, vector search, and knowledge-management architectures.
• Experience implementing systematic LLM evaluation and guardrails.
• Experience with AWS AI/ML services.
• Experience with time-series analytics and anomaly detection.
• Experience with industrial, energy, renewable-generation, BESS, or operational datasets.
• Familiarity with MLOps and model-monitoring practices.

Role timeline and logistics

• Location: United States (onsite)
• Start and end date: 22 Oct 2026 to 21 Oct 2027
• Indicative hourly rate: USD 100 to 105/hr
• Respond by: 10 Oct 2026