AI/M Engineer - Generative AI, Agentic AI & MLOps

ScolerTec Inc; Stati Uniti; In loco; USD 180.000 - 280.000; Tempo pieno

Descrizione del lavoro

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

Key responsibilities include building end-to-end ML systems, evaluating models, and implementing responsible AI with robust governance artifacts in fast-paced environments. Collaboration across teams is essential to deliver scalable AI platforms.

Competenze

• 10+ years specialized experience at expert level in ML/AI.
• Strong background in ML/DL/NLP and manufacturing robust models.
• Proficiency in Python and SQL for data processing and modeling.
• Hands-on with TensorFlow, PyTorch, and related frameworks.
• Experience with MLOps/LLMOps and model governance.

Mansioni

• Design and deploy ML, GenAI, and forecasting solutions.
• Develop LLM applications, RAG pipelines, and AI agents.
• Evaluate foundation and open-source/commercial models.
• Build MLOps/LLMOps pipelines and automate lifecycle workflows.
• Monitor drift, retrain models, and ensure security and governance.
• Address biases, privacy, and data leakage concerns.
• Maintain model cards and governance artifacts.
• Recommend AI tooling and reusable architectures.

Conoscenze

Python

SQL

ML/DL/NLP

TensorFlow

PyTorch

scikit-learn

XGBoost

MLOps/LLMOps

Responsible AI

Strumenti

scikit-learn

XGBoost

Descrizione del lavoro

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