Key Responsibilities

• Build and maintain production-grade ML and AI systems
• Design and implement agent patterns including tool use, function calling, planning, and memory
• Work with unstructured data and images at scale
• Train, tune, and evaluate machine learning and deep learning models
• Deploy AI systems on AWS, GCP, or Azure using microservices architectures
• Build NLP solutions and parse PDF/text documents
• Apply statistical and ML techniques including regression, neural nets, decision trees, SVM, and ensembles

Requirements

• 8+ years of experience building production ML/AI systems
• Recent experience with LLMs or AI agents in data science
• Strong Python engineering skills with clean, scalable, maintainable code
• Proven experience with unstructured data and images at scale
• Hands-on experience with agent patterns (tool use, function calling, planning, memory)
• Proficiency with Scikit-Learn, NumPy, SciPy, and Pandas
• Strong understanding of ML model training and hyperparameter tuning
• Working knowledge of deep learning models, loss functions, and accuracy measures
• Hands-on proficiency with PyTorch, TensorFlow, or Keras
• Experience with NLP solutions preferred
• Experience parsing PDF and text documents preferred
• Multi-cloud experience with AWS, GCP, or Azure
• Comfortable working in a microservices environment
• Self-motivated with enthusiasm to build next-generation AI systems

Skills Required