AI/ML Engineer / Data Scientist

• 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.

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.

Everforth Apex is a world-class IT services company that serves thousands of clients across the globe. When you join Everforth Apex, you become part of a team that values innovation, collaboration, and continuous learning. We offer quality career resources, training, certifications, development opportunities, and a comprehensive benefits package. Our commitment to excellence is reflected in many awards, including ClearlyRateds Best of Staffing in Talent Satisfaction in the United States and Great Place to Work in the United Kingdom and Mexico.

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