Description

You will build and maintain advanced AI systems using Python and modern ML/Gen AI techniques.

Responsibilities

• Design and implement agentic AI systems using frameworks like CrewAI or AutoGen for complex workflows.
• Develop and maintain ML/MLOps pipelines covering training, deployment, and monitoring.
• Integrate semantic models into data mesh architectures, ensuring domain interoperability.
• Apply ML to solve business problems, including anomaly detection and regulatory reporting.
• Design and evolve cloud-native, modular architectures capable of scaling and maintaining resilience.

Required Skills

• 10+ years of professional experience.
• Strong background in ML/NLP, including transformers, embeddings, and supervised/unsupervised learning.
• Hands-on proficiency with PyTorch, TensorFlow, and scikit-learn.
• Experience building and maintaining MLOps pipelines using MLflow, Kubeflow, or SageMaker.
• Proficiency in Python.
• Knowledge of system architecture, object-oriented design, and design patterns.
• Familiarity with capital markets datasets and financial standards.
• Experience with cloud platforms (AWS, Azure) and Infrastructure as Code (Terraform, CloudFormation).
• Understanding of explainable AI (XAI) techniques like SHAP or LIME.

Key Skills

Education

Any Gradute