Sr. AI Engineer

• Monitor and improve model performance, accuracy, and scalability.
• Implement best practices for MLOps, model monitoring, and governance.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field.
• 8+ years of experience in software development with 4+ years in AI/ML engineering.
• Strong programming experience in Python.
• Hands-on experience with machine learning and deep learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Experience working with large datasets and distributed data processing systems.
• Knowledge of natural language processing (NLP), computer vision, or generative AI.
• Experience deploying AI models using Docker, Kubernetes, or cloud platforms.

Preferred Qualifications

• Experience with Large Language Models (LLMs) and Generative AI.
• Experience with ML lifecycle tools such as MLflow, Kubeflow, or Airflow.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Knowledge of vector databases and embedding models.
• Familiarity with CI/CD pipelines and DevOps practices.

Technical Skills

• Programming: Python, SQL
• ML Frameworks: TensorFlow, PyTorch, Scikit-learn
• AI Domains: NLP, Computer Vision, Generative AI
• MLOps Tools: MLflow, Kubeflow, Airflow
• Cloud Platforms: AWS, Azure, GCP
• Containers: Docker, Kubernetes

Soft Skills

• Strong analytical and problem-solving skills
• Excellent communication and collaboration skills
• Ability to work in a fast-paced and innovative environment
• Strong mentoring and leadership abilities

Salary Range

$140,000 – $190,000 per year (depending on experience and location).

If you want, I can also give:

• Short recruiter version (5 lines JD for Dice/LinkedIn posting)
• Boolean search string for AI Engineer sourcing
• AI/ML Engineer vs AI Engineer JD difference
• GenAI Engineer JD (very in-demand in 2025).