AI/ML Engineer – Generative AI, Agentic AI & MLOps

ScolerTec Inc; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

ScolerTec Inc. is actively seeking seasoned AI/ML Engineers to design, deploy, and govern production AI/ML solutions, including Generative AI, LLM applications, RAG pipelines, and forecasting models.

You will build ML/Ops pipelines, automate end-to-end ML workflows, monitor drift, ensure responsible AI, and address model-risk issues while maintaining governance artifacts across projects.

Qualifications

• 10+ years specialized experience in ML/DL/NLP.
• Proficiency with Python and SQL for model development and data handling.
• Experience with TensorFlow or PyTorch and scikit-learn or XGBoost.
• Hands-on with MLOps/LLMOps pipelines and model governance.

Responsibilities

• Design and deploy ML, GenAI, and forecasting solutions.
• Develop LLM applications, RAG pipelines, and AI agents.
• Evaluate foundation models and manage model drift and bias.

Skills

Python

SQL

TensorFlow

PyTorch

scikit-learn

MLOps

Responsible AI

Tools

AWS ML Specialty

Google Professional ML Engineer

Job description

ScolerTec is seeking multiple AI/ML Engineers to design, develop, deploy, and govern production AI/ML solutions, including Generative AI, Agentic AI, LLM applications, RAG pipelines, predictive models, forecasting, and advanced analytics.

Key Responsibilities

• Design and deploy ML, GenAI, Agentic AI, predictive, and forecasting solutions.
• Develop LLM applications, RAG pipelines, and AI agents.
• Evaluate foundation and open-source/commercial models.
• Build MLOps/LLMOps pipelines.
• Automate training, testing, deployment, monitoring, rollback, and retraining.
• Monitor model drift and degradation.
• Implement Responsible AI, explainability, bias testing, privacy, and security.
• Address hallucination, prompt injection, data leakage, and model-risk issues.
• Maintain model cards and AI governance artifacts.
• Recommend AI tooling and reusable architectures.

Qualifications

• 10+ years specialized experience at the required expert level.
• Machine learning/deep learning/NLP.
• Python, SQL.
• TensorFlow, PyTorch, scikit-learn or XGBoost.
• MLOps/LLMOps.
• Responsible AI/governance.
• AWS ML Specialty or Google Professional ML Engineer