Role overview
Strong expertise in Artificial Intelligence and Machine Learning, including:
- Natural Language Processing (NLP)
- Computer Vision (CV)
- Generative AI
- Deep Learning
Hands-on experience working with:
- Large Language Models (LLMs)
- Prompt engineering and model fine-tuning
- Multi-agent AI architectures
- Model optimization and inference efficiency
Experience building and deploying production-scale machine learning systems
Proficiency with modern ML frameworks and ecosystems such as:
- Python
- PyTorch or TensorFlow
- Hugging Face
- LangChain or similar LLM frameworks
Familiarity with MLOps practices, scalable AI infrastructure, and data pipelines
What you'll work on
- Designing and developing advanced machine learning and deep learning models
- Building solutions leveraging Large Language Models (LLMs), Generative AI, NLP, and Computer Vision
- Architecting scalable AI and ML pipelines from experimentation through production deployment
- Developing and optimizing models through fine-tuning, prompt engineering, and inference optimization
- Building end-to-end machine learning workflows including data ingestion, feature engineering, training, evaluation, deployment, and monitoring
- Translating complex data science methodologies into actionable insights and business strategies
- Partnering with business leaders to identify opportunities where AI can drive innovation and operational efficiency
- Communicating technical concepts and model outcomes to both technical and non-technical stakeholders
- Mentoring data scientists and helping establish **best practices for model development and MLOps
What we're looking for
Master’s or Ph.D. in a quantitative field such as:
- Computer Science
- Data Science
- Statistics
- Engineering
- Applied Mathematics
- Economics
Experience developing and deploying Generative AI or deep learning models in production environments
Experience working with **large-scale datasets and enterprise AI platforms