Position Overview

We are seeking an experienced Applied AI/ML Engineer and Data Scientist to develop and operationalize the intelligence layer of NextBrain. This senior, hands-on role combines data science, machine learning, generative AI, and software engineering to create intelligent capabilities that help users understand operational data, diagnose issues, identify anomalies, retrieve knowledge, and make informed decisions.

Unlike a traditional research-focused Data Scientist position, this role emphasizes taking AI and machine-learning solutions from early experimentation through production deployment, evaluation, monitoring, and continuous improvement.

Key Responsibilities

• Design, develop, evaluate, and deploy AI and machine-learning capabilities within NextBrain.
• Develop analytical models for anomaly detection, asset health, forecasting, classification, and other operational use cases.
• Build generative AI and agentic capabilities using enterprise-approved foundation models and AI platforms.
• Design prompts, tools, agents, workflows, and orchestration patterns.
• Develop Retrieval-Augmented Generation solutions and knowledge-retrieval capabilities when appropriate.
• Create rigorous evaluation frameworks for large language model and agent performance.
• Establish metrics for model accuracy, relevance, reliability, hallucination rates, latency, and cost.
• Develop guardrails and validation mechanisms for AI-generated responses.
• Partner with Data Engineering teams to define training, inference, retrieval, feature, and data requirements.
• Collaborate with Full Stack and Cloud Engineers to deploy AI services into production.
• Rapidly develop prototypes while ensuring solutions can transition successfully into production environments.
• Monitor model and agent performance and continuously improve deployed capabilities.
• Communicate model behavior, limitations, and analytical findings to engineers, product stakeholders, and operational subject-matter experts.
• Evaluate emerging AI, agentic AI, machine-learning, and data-science technologies for potential enterprise applications.

Required Qualifications

• Bachelor’s or master’s degree in Computer Science, Data Science, Engineering, Statistics, Machine Learning, or a related field. Equivalent professional experience may be considered.
• Four or more years of experience developing machine-learning or advanced analytics solutions.
• Strong Python programming skills.
• Experience with commonly used machine-learning and data-science frameworks and libraries.
• Demonstrated experience moving analytical or machine-learning solutions from experimentation into production.
• Strong foundation in statistics, experimentation, model evaluation, and data analysis.
• Experience working with cloud-based data and computing environments.
• Working knowledge of APIs, software-development practices, source control, and CI/CD.
• Demonstrated ability to translate business or operational challenges into effective analytical solutions.

Preferred Qualifications

• Hands-on experience developing applications powered by large language models.
• Experience with agentic frameworks, tool calling, Model Context Protocol, or similar AI orchestration technologies.
• Experience with Retrieval-Augmented Generation, embeddings, vector search, and knowledge-management architectures.
• Experience developing systematic LLM evaluation methods and AI guardrails.
• Experience with AWS artificial intelligence and machine-learning services.
• Experience with time-series analytics, forecasting, and anomaly detection.
• Experience working with industrial, energy, renewable-generation, battery energy-storage, or other operational datasets.
• Familiarity with MLOps, model monitoring, and production AI governance practices.

What Success Looks Like

The successful candidate will help advance NextBrain from a platform that provides access to applications and data into an intelligent operational assistant. Its AI capabilities must remain measurable, secure, reliable, and trustworthy for enterprise operational use, with explainable outputs where required.

Ideal Candidate

The ideal candidate is a senior, hands-on AI professional who can combine analytical expertise with practical software-development skills. This individual can move quickly from problem definition and prototyping to secure, scalable production deployment while collaborating effectively across technical and operational teams.