Python AI Engineer

Morgan Stanley
Atlanta, United States of America
31 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Atlanta, United States of America

Tech stack

API
Artificial Intelligence
Amazon Web Services (AWS)
Azure
Cloud Computing
Software Quality
Data Structures
Python
Machine Learning
NumPy
Performance Tuning
TensorFlow
Software Engineering
Data Streaming
Data Processing
Google Cloud Platform
PyTorch
Delivery Pipeline
Large Language Models
Spark
Deep Learning
Generative AI
Pandas
Scikit Learn
Kubernetes
Real Time Data
Machine Learning Operations
REST
Docker
Microservices

Job description

Morgan Stanley is seeking a highly experienced Senior Python AI Engineer with deep expertise in building scalable AI/ML solutions. The ideal candidate will have over 15 years of experience in software development, with strong hands-on experience in Python and modern AI frameworks., * Design and develop scalable AI/ML solutions using Python

  • Build and optimize machine learning and deep learning models
  • Work with large-scale structured and unstructured datasets
  • Develop APIs and microservices for AI-based applications
  • Collaborate with cross-functional teams including data engineers, quants, and business stakeholders
  • Implement best practices for model deployment, monitoring, and performance tuning
  • Ensure code quality, security, and compliance with enterprise standards
  • Mentor junior developers and provide technical leadership

Requirements

  • 15+ years of experience in software development
  • Strong expertise in Python and AI/ML development
  • Hands-on experience with frameworks like TensorFlow, PyTorch, Scikit-learn
  • Experience with NLP, LLMs, or Generative AI
  • Strong knowledge of data structures, algorithms, and system design
  • Experience with REST APIs and microservices architecture
  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud Platform)
  • Experience with data processing tools like Pandas, NumPy, Spark
  • Strong problem-solving and analytical skills, * Experience in financial services or investment banking
  • Knowledge of quantitative modeling or risk systems
  • Exposure to MLOps tools (Docker, Kubernetes, CI/CD pipelines)
  • Experience with real-time data processing and streaming technologies

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