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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Engineer / Data Scientist - **Company:** Everforth Apex - **Location:** Juno Beach, FL, United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Cloud Database, Cloud Engineering, Continuous Integration, Information Engineering, Python (Programming Language), Knowledge Management, Machine Learning, Azure Machine Learning, Search Technologies, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Model Validation, Software Application Programming, AI Platforms, Information Technology, Machine Learning Operations, Software Version Control - **Published:** September 15, 2026 - **Apply:** https://www.dice.com/job-detail/d3b794e3-2b13-4c0f-b430-b796fcc0852e ## About the Role Education: A Master's degree or Bachelor's degree with equivalent experience in Computer Science, Data Science, Engineering, Statistics, Machine Learning, or a related discipline is required. Experience: A minimum of 4+ years of experience developing machine-learning or advanced analytics solutions is necessary. Experience taking analytical or ML solutions from experimentation into production is also required. Technical Skills: Strong Python skills are required, along with experience with common ML/data-science frameworks and libraries. Candidates must have a strong foundation in statistics, experimentation, model evaluation, and data analysis. Experience with cloud-based data and compute environments, APIs, software-development practices, source control, and CI/CD is also needed. A demonstrated ability to translate business or operational problems into analytical approaches is essential. Preferred Qualifications * 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. ## Description * Design, develop, evaluate, and deploy AI/ML capabilities. * Develop analytical models for anomaly detection, asset health, forecasting, classification, and other operational use cases. * Develop 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 and knowledge-retrieval solutions when appropriate. * Create rigorous evaluation frameworks for LLM and agent behavior. * Establish metrics for model accuracy, relevance, reliability, hallucination, latency, and cost. * Develop guardrails and validation mechanisms for AI-generated responses. * Collaborate with Data Engineering to define training, inference, retrieval, and feature-data requirements. * Collaborate with the Full Stack/Cloud Engineer to deploy AI services into production. * Develop prototypes rapidly 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. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [This App Reached 10,000 Users in One Week. 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