Staff AI Engineer

We are seeking a mid-level AI Engineer to join our team focused on building scalable, production-ready AI solutions that support analytics, automation, and intelligent decision-making. This role will contribute to the development and deployment of machine learning models, generative AI systems, and AI-enhanced data workflows across platforms.

Key Responsibilities

• Model Development & Deployment

  : Design, train, and deploy machine learning and deep learning models using frameworks like TensorFlow, PyTorch, and Scikit-learn.

• Generative AI & LLMs

  : Implement and fine-tune large language models (LLMs) using tools such as LangChain, RAG, and vector databases. Experience with GPTs, LLaMA, or similar models is preferred

• MLOps & GenAIOps

  : Use tools like MLflow and Docker to manage model lifecycle, reproducibility, and scalability. Support production-grade GenAI systems

• Data Engineering Collaboration

  : Work closely with data engineers to ensure robust data pipelines and infrastructure for model training and inference.

• Integration & APIs

  : Develop APIs and microservices to integrate AI models into enterprise applications and workflows.

• Monitoring & Optimization

  : Continuously monitor model performance and retrain as needed to maintain accuracy and relevance.

• Security & Governance

  : Ensure AI systems comply with enterprise security and data governance standards.

Skills & Qualifications

• 812 years of experience in AI/ML engineering or related roles.
• Proficiency in Python and experience with AI frameworks (TensorFlow, PyTorch).
• Familiarity with cloud platforms (AWS, Azure, GCP) for model deployment.
• Experience with MLOps tools (MLflow, Docker) and GenAI deployment.
• Strong understanding of LLMs, NLP, and computer vision techniques.
• Ability to write clean, efficient, and reusable code.
• Experience with RESTful APIs and microservices architecture.

Preferred Experience

• Exposure to educational technology or enterprise data environments.
• Experience integrating AI into transactional systems.
• Familiarity with data warehouses and data governance frameworks.