About Us:
As a Senior AI Engineer at Kenility, you’ll join a tight-knit family of creative developers, engineers, and designers who strive to develop and deliver the highest quality products into the market.
Technical Requirements:
- Bachelor’s degree in Computer Science, Software Engineering, or a related field.
- More than 5 years of experience developing machine learning systems in production environments.
- Strong programming skills in Python and solid experience with frameworks such as PyTorch, TensorFlow, or Scikit-learn.
- Demonstrated ability to deploy, monitor, and improve AI models in real-world applications.
- Proven experience with advanced AI/ML modeling techniques.
- Familiarity with large language model APIs (such as OpenAI or Claude) in production use cases.
- In-depth understanding of machine learning fundamentals including supervised/unsupervised learning and evaluation methodologies.
- Hands-on experience deploying AI/ML workloads on AWS, with a focus on scalability and performance.
- Comfortable working independently and driving initiatives across the full AI lifecycle.
- Effective communicator with experience collaborating directly with senior stakeholders in cross-functional settings.
- Desirable experience with computer vision techniques (object detection, OCR, image segmentation).
- Familiarity with RAG architectures and vector database implementations.
- Experience optimizing and engineering prompts for LLM applications.
- Knowledge of SQL and data analytics.
- Background in EdTech or educational content platforms is a plus.
- Minimum Upper Intermediate English (B2) or Proficient (C1).
Tasks and Responsibilities:
- Design, develop, and deploy AI-powered systems that automate content creation and enhance educational experiences.
- Lead AI initiatives independently, collaborating closely with clients and internal engineering teams.
- Build production-ready ML models for tasks such as classification, computer vision, and content generation.
- Develop systems for tagging educational content by subject, grade level, and standards.
- Create computer vision pipelines to digitize scanned worksheets with high accuracy.
- Implement RAG-based architectures using large content repositories to generate contextually relevant materials.
- Engineer and refine prompts to optimize the performance and accuracy of LLM outputs.
- Develop AI systems for validating content quality using educational taxonomies.
- Build autonomous agentic workflows that generate lesson plans, worksheets, and evaluations from teacher inputs.
- Analyze student work to detect learning gaps and misconceptions through AI-driven models.
- Operate and monitor AI services in AWS environments with attention to cost, performance, and reliability.
- Define and support strategies for data labeling and feedback collection to enhance model performance.
- Document AI pipelines, models, and systems clearly for internal stakeholders.
- Participate in code reviews and promote best practices in AI engineering.
Soft Skills:
- Responsibility
- Proactivity
- Flexibility
- Great communication skills
